MERN Stack with Blog Project
Wednesday, September 29, 2021
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MERN Stack with Blog Project - Learn, Apply, Build a Blog Project using NodeJs, Express, MongoDB & React
- Hot & New
- Created by Tech Academy
- English [Auto]
What you'll learn
- Build a full stack Blog application with React, Redux, Node, Express & MongoDB
- Integrate React with an Express backend in an elegant way
- Create an extensive backend API with Express
- React Hooks, Async/Await & modern practices
Description
Welcome to "MERN Stack with Blog Project". In this course, we will be building an in-depth full-stack Blog project application using Node.js, Express, React, and MongoDB along with ES6+. We will start with a blank text editor and end with a deployed full-stack application. This course includes...
Building an extensive backend API with Node.js & Express
Extensive API testing with Postman
Integrating React with our backend in an elegant way, creating a great workflow
Building our frontend to work with the API
Get and Post Request using MongoDB
This course project is probably the biggest and most exciting project you have built so far. It is packed with hundreds of tips and tricks that can help you build almost any type of full-stack app (not limited to this blog project).
Master the art of building FullStack/MERN Stack apps by enrolling in this course and never look back. What you are now and what you will become after completing this course is going to be a groundbreaking step in your web development career.
You can build the biggest and most complex apps of your dream or as required at your job. Master the stack of all stacks and become the most productive and innovative developer of your team. I welcome you to be a part of this incredible journey.
Who this course is for:
- Anyone that wants to learn how to build and deploy a full stack MERN application
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Java Data Structures and Algorithms Masterclass
Free Udemy Coupon
Java Data Structures and Algorithms Masterclass - Data Structures and Algorithms from Zero to Hero and Crack Top Companies 100+ Interview questions (Java Coding)
- Created by Elshad Karimov
- English [Auto]
What you'll learn
- Learn, implement, and use different Data Structures
- Learn, implement and use different Algorithms
- Become a better developer by mastering computer science fundamentals
- Learn everything you need to ace difficult coding interviews
- Cracking the Coding Interview with 100+ questions with explanations
- Time and Space Complexity of Data Structures and Algorithms
- Recursion
- Big O
- Dynamic Programming
- Divide and Conquer Algorithms
- Graph Algorithms
- Greedy Algorithms
Description
Welcome to the Java Data Structures and Algorithms Masterclass, the most modern, and the most complete Data Structures and Algorithms in Java course on the internet.
At 44+ hours, this is the most comprehensive course online to help you ace your coding interviews and learn about Data Structures and Algorithms in Java. You will see 100+ Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft and how to face Interviews with comprehensive visual explanatory video materials which will bring you closer towards landing the tech job of your dreams!
Learning Java is one of the fastest ways to improve your career prospects as it is one of the most in demand tech skills! This course will help you in better understanding every detail of Data Structures and how algorithms are implemented in high level programming language.
We'll take you step-by-step through engaging video tutorials and teach you everything you need to succeed as a professional programmer.
After finishing this course, you will be able to:
Learn basic algorithmic techniques such as greedy algorithms, binary search, sorting and dynamic programming to solve programming challenges.
Learn the strengths and weaknesses of a variety of data structures, so you can choose the best data structure for your data and applications
Learn many of the algorithms commonly used to sort data, so your applications will perform efficiently when sorting large datasets
Learn how to apply graph and string algorithms to solve real-world challenges: finding shortest paths on huge maps and assembling genomes from millions of pieces.
Why this course is so special and different from any other resource available online?
This course will take you from very beginning to a very complex and advanced topics in understanding Data Structures and Algorithms!
You will get video lectures explaining concepts clearly with comprehensive visual explanations throughout the course.
You will also see Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft.
I cover everything you need to know about technical interview process!
So whether you are interested in learning the top programming language in the world in-depth and interested in learning the fundamental Algorithms, Data Structures and performance analysis that make up the core foundational skillset of every accomplished programmer/designer or software architect and is excited to ace your next technical interview this is the course for you!
And this is what you get by signing up today:
Lifetime access to 44+ hours of HD quality videos. No monthly subscription. Learn at your own pace, whenever you want
Friendly and fast support in the course Q&A whenever you have questions or get stuck
FULL money back guarantee for 30 days!
This course is designed to help you to achieve your career goals. Whether you are looking to get more into Data Structures and Algorithms , increase your earning potential or just want a job with more freedom, this is the right course for you!
The topics that are covered in this course.
Section 1 - Introduction
What are Data Structures?
What is an algorithm?
Why are Data Structures and Algorithms important?
Types of Data Structures
Types of Algorithms
Section 2 - Recursion
What is Recursion?
Why do we need recursion?
How Recursion works?
Recursive vs Iterative Solutions
When to use/avoid Recursion?
How to write Recursion in 3 steps?
How to find Fibonacci numbers using Recursion?
Section 3 - Cracking Recursion Interview Questions
Question 1 - Sum of Digits
Question 2 - Power
Question 3 - Greatest Common Divisor
Question 4 - Decimal To Binary
Section 4 - Bonus CHALLENGING Recursion Problems (Exercises)
power
factorial
productofArray
recursiveRange
fib
reverse
isPalindrome
someRecursive
flatten
captalizeFirst
nestedEvenSum
capitalizeWords
stringifyNumbers
collectStrings
Section 5 - Big O Notation
Analogy and Time Complexity
Big O, Big Theta and Big Omega
Time complexity examples
Space Complexity
Drop the Constants and the non dominant terms
Add vs Multiply
How to measure the codes using Big O?
How to find time complexity for Recursive calls?
How to measure Recursive Algorithms that make multiple calls?
Section 6 - Top 10 Big O Interview Questions (Amazon, Facebook, Apple and Microsoft)
Product and Sum
Print Pairs
Print Unordered Pairs
Print Unordered Pairs 2 Arrays
Print Unordered Pairs 2 Arrays 100000 Units
Reverse
O(N) Equivalents
Factorial Complexity
Fibonacci Complexity
Powers of 2
Section 7 - Arrays
What is an Array?
Types of Array
Arrays in Memory
Create an Array
Insertion Operation
Traversal Operation
Accessing an element of Array
Searching for an element in Array
Deleting an element from Array
Time and Space complexity of One Dimensional Array
One Dimensional Array Practice
Create Two Dimensional Array
Insertion - Two Dimensional Array
Accessing an element of Two Dimensional Array
Traversal - Two Dimensional Array
Searching for an element in Two Dimensional Array
Deletion - Two Dimensional Array
Time and Space complexity of Two Dimensional Array
When to use/avoid array
Section 8 - Cracking Array Interview Questions (Amazon, Facebook, Apple and Microsoft)
Question 1 - Missing Number
Question 2 - Pairs
Question 3 - Finding a number in an Array
Question 4 - Max product of two int
Question 5 - Is Unique
Question 6 - Permutation
Question 7 - Rotate Matrix
Section 9 - CHALLENGING Array Problems (Exercises)
Middle Function
2D Lists
Best Score
Missing Number
Duplicate Number
Pairs
Section 10 - Linked List
What is a Linked List?
Linked List vs Arrays
Types of Linked List
Linked List in the Memory
Creation of Singly Linked List
Insertion in Singly Linked List in Memory
Insertion in Singly Linked List Algorithm
Insertion Method in Singly Linked List
Traversal of Singly Linked List
Search for a value in Single Linked List
Deletion of node from Singly Linked List
Deletion Method in Singly Linked List
Deletion of entire Singly Linked List
Time and Space Complexity of Singly Linked List
Section 11 - Circular Singly Linked List
Creation of Circular Singly Linked List
Insertion in Circular Singly Linked List
Insertion Algorithm in Circular Singly Linked List
Insertion method in Circular Singly Linked List
Traversal of Circular Singly Linked List
Searching a node in Circular Singly Linked List
Deletion of a node from Circular Singly Linked List
Deletion Algorithm in Circular Singly Linked List
Method in Circular Singly Linked List
Deletion of entire Circular Singly Linked List
Time and Space Complexity of Circular Singly Linked List
Section 12 - Doubly Linked List
Creation of Doubly Linked List
Insertion in Doubly Linked List
Insertion Algorithm in Doubly Linked List
Insertion Method in Doubly Linked List
Traversal of Doubly Linked List
Reverse Traversal of Doubly Linked List
Searching for a node in Doubly Linked List
Deletion of a node in Doubly Linked List
Deletion Algorithm in Doubly Linked List
Deletion Method in Doubly Linked List
Deletion of entire Doubly Linked List
Time and Space Complexity of Doubly Linked List
Section 13 - Circular Doubly Linked List
Creation of Circular Doubly Linked List
Insertion in Circular Doubly Linked List
Insertion Algorithm in Circular Doubly Linked List
Insertion Method in Circular Doubly Linked List
Traversal of Circular Doubly Linked List
Reverse Traversal of Circular Doubly Linked List
Search for a node in Circular Doubly Linked List
Delete a node from Circular Doubly Linked List
Deletion Algorithm in Circular Doubly Linked List
Deletion Method in Circular Doubly Linked List
Entire Circular Doubly Linked List
Time and Space Complexity of Circular Doubly Linked List
Time Complexity of Linked List vs Arrays
Section 14 - Cracking Linked List Interview Questions (Amazon, Facebook, Apple and Microsoft)
Linked List Class
Question 1 - Remove Dups
Question 2 - Return Kth to Last
Question 3 - Partition
Question 4 - Sum Linked Lists
Question 5 - Intersection
Section 15 - Stack
What is a Stack?
What and Why of Stack?
Stack Operations
Stack using Array vs Linked List
Stack Operations using Array (Create, isEmpty, isFull)
Stack Operations using Array (Push, Pop, Peek, Delete)
Time and Space Complexity of Stack using Array
Stack Operations using Linked List
Stack methods - Push , Pop, Peek, Delete and isEmpty using Linked List
Time and Space Complexity of Stack using Linked List
When to Use/Avoid Stack
Stack Quiz
Section 16 - Queue
What is a Queue?
Linear Queue Operations using Array
Create, isFull, isEmpty and enQueue methods using Linear Queue Array
Dequeue, Peek and Delete Methods using Linear Queue Array
Time and Space Complexity of Linear Queue using Array
Why Circular Queue?
Circular Queue Operations using Array
Create, Enqueue, isFull and isEmpty Methods in Circular Queue using Array
Dequeue, Peek and Delete Methods in Circular Queue using Array
Time and Space Complexity of Circular Queue using Array
Queue Operations using Linked List
Create, Enqueue and isEmpty Methods in Queue using Linked List
Dequeue, Peek and Delete Methods in Queue using Linked List
Time and Space Complexity of Queue using Linked List
Array vs Linked List Implementation
When to Use/Avoid Queue?
Section 17 - Cracking Stack and Queue Interview Questions (Amazon,Facebook, Apple, Microsoft)
Question 1 - Three in One
Question 2 - Stack Minimum
Question 3 - Stack of Plates
Question 4 - Queue via Stacks
Question 5 - Animal Shelter
Section 18 - Tree / Binary Tree
What is a Tree?
Why Tree?
Tree Terminology
How to create a basic tree in Java?
Binary Tree
Types of Binary Tree
Binary Tree Representation
Create Binary Tree (Linked List)
PreOrder Traversal Binary Tree (Linked List)
InOrder Traversal Binary Tree (Linked List)
PostOrder Traversal Binary Tree (Linked List)
LevelOrder Traversal Binary Tree (Linked List)
Searching for a node in Binary Tree (Linked List)
Inserting a node in Binary Tree (Linked List)
Delete a node from Binary Tree (Linked List)
Delete entire Binary Tree (Linked List)
Create Binary Tree (Array)
Insert a value Binary Tree (Array)
Search for a node in Binary Tree (Array)
PreOrder Traversal Binary Tree (Array)
InOrder Traversal Binary Tree (Array)
PostOrder Traversal Binary Tree (Array)
Level Order Traversal Binary Tree (Array)
Delete a node from Binary Tree (Array)
Entire Binary Tree (Array)
Linked List vs Python List Binary Tree
Section 19 - Binary Search Tree
What is a Binary Search Tree? Why do we need it?
Create a Binary Search Tree
Insert a node to BST
Traverse BST
Search in BST
Delete a node from BST
Delete entire BST
Time and Space complexity of BST
Section 20 - AVL Tree
What is an AVL Tree?
Why AVL Tree?
Common Operations on AVL Trees
Insert a node in AVL (Left Left Condition)
Insert a node in AVL (Left Right Condition)
Insert a node in AVL (Right Right Condition)
Insert a node in AVL (Right Left Condition)
Insert a node in AVL (all together)
Insert a node in AVL (method)
Delete a node from AVL (LL, LR, RR, RL)
Delete a node from AVL (all together)
Delete a node from AVL (method)
Delete entire AVL
Time and Space complexity of AVL Tree
Section 21 - Binary Heap
What is Binary Heap? Why do we need it?
Common operations (Creation, Peek, sizeofheap) on Binary Heap
Insert a node in Binary Heap
Extract a node from Binary Heap
Delete entire Binary Heap
Time and space complexity of Binary Heap
Section 22 - Trie
What is a Trie? Why do we need it?
Common Operations on Trie (Creation)
Insert a string in Trie
Search for a string in Trie
Delete a string from Trie
Practical use of Trie
Section 23 - Hashing
What is Hashing? Why do we need it?
Hashing Terminology
Hash Functions
Types of Collision Resolution Techniques
Hash Table is Full
Pros and Cons of Resolution Techniques
Practical Use of Hashing
Hashing vs Other Data structures
Section 24 - Sort Algorithms
What is Sorting?
Types of Sorting
Sorting Terminologies
Bubble Sort
Selection Sort
Insertion Sort
Bucket Sort
Merge Sort
Quick Sort
Heap Sort
Comparison of Sorting Algorithms
Section 25 - Searching Algorithms
Introduction to Searching Algorithms
Linear Search
Linear Search in Python
Binary Search
Binary Search in Python
Time Complexity of Binary Search
Section 26 - Graph Algorithms
What is a Graph? Why Graph?
Graph Terminology
Types of Graph
Graph Representation
Graph in Java using Adjacency Matrix
Graph in Java using Adjacency List
Section 27 - Graph Traversal
Breadth First Search Algorithm (BFS)
Breadth First Search Algorithm (BFS) in Java - Adjacency Matrix
Breadth First Search Algorithm (BFS) in Java - Adjacency List
Time Complexity of Breadth First Search (BFS) Algorithm
Depth First Search (DFS) Algorithm
Depth First Search (DFS) Algorithm in Java - Adjacency List
Depth First Search (DFS) Algorithm in Java - Adjacency Matrix
Time Complexity of Depth First Search (DFS) Algorithm
BFS Traversal vs DFS Traversal
Section 28 - Topological Sort
What is Topological Sort?
Topological Sort Algorithm
Topological Sort using Adjacency List
Topological Sort using Adjacency Matrix
Time and Space Complexity of Topological Sort
Section 29 - Single Source Shortest Path Problem
SWhat is Single Source Shortest Path Problem?
Breadth First Search (BFS) for Single Source Shortest Path Problem (SSSPP)
BFS for SSSPP in Java using Adjacency List
BFS for SSSPP in Java using Adjacency Matrix
Time and Space Complexity of BFS for SSSPP
Why does BFS not work with Weighted Graph?
Why does DFS not work for SSSP?
Section 30 - Dijkstra's Algorithm
Dijkstra's Algorithm for SSSPP
Dijkstra's Algorithm in Java - 1
Dijkstra's Algorithm in Java - 2
Dijkstra's Algorithm with Negative Cycle
Section 31 - Bellman Ford Algorithm
Bellman Ford Algorithm
Bellman Ford Algorithm with negative cycle
Why does Bellman Ford run V-1 times?
Bellman Ford in Python
BFS vs Dijkstra vs Bellman Ford
Section 32 - All Pairs Shortest Path Problem
All pairs shortest path problem
Dry run for All pair shortest path
Section 33 - Floyd Warshall
Floyd Warshall Algorithm
Why Floyd Warshall?
Floyd Warshall with negative cycle,
Floyd Warshall in Java,
BFS vs Dijkstra vs Bellman Ford vs Floyd Warshall,
Section 34 - Minimum Spanning Tree
Minimum Spanning Tree,
Disjoint Set,
Disjoint Set in Java,
Section 35 - Kruskal's and Prim's Algorithms
Kruskal Algorithm,
Kruskal Algorithm in Python,
Prim's Algorithm,
Prim's Algorithm in Python,
Prim's vs Kruskal
Section 36 - Cracking Graph and Tree Interview Questions (Amazon,Facebook, Apple, Microsoft)
Section 37 - Greedy Algorithms
What is Greedy Algorithm?
Well known Greedy Algorithms
Activity Selection Problem
Activity Selection Problem in Python
Coin Change Problem
Coin Change Problem in Python
Fractional Knapsack Problem
Fractional Knapsack Problem in Python
Section 38 - Divide and Conquer Algorithms
What is a Divide and Conquer Algorithm?
Common Divide and Conquer algorithms
How to solve Fibonacci series using Divide and Conquer approach?
Number Factor
Number Factor in Java
House Robber
House Robber Problem in Java
Convert one string to another
Convert One String to another in Java
Zero One Knapsack problem
Zero One Knapsack problem in Java
Longest Common Sequence Problem
Longest Common Subsequence in Java
Longest Palindromic Subsequence Problem
Longest Palindromic Subsequence in Java
Minimum cost to reach the Last cell problem
Minimum Cost to reach the Last Cell in 2D array using Java
Number of Ways to reach the Last Cell with given Cost
Number of Ways to reach the Last Cell with given Cost in Java
Section 39 - Dynamic Programming
What is Dynamic Programming? (Overlapping property)
Where does the name of DC come from?
Top Down with Memoization
Bottom Up with Tabulation
Top Down vs Bottom Up
Is Merge Sort Dynamic Programming?
Number Factor Problem using Dynamic Programming
Number Factor : Top Down and Bottom Up
House Robber Problem using Dynamic Programming
House Robber : Top Down and Bottom Up
Convert one string to another using Dynamic Programming
Convert String using Bottom Up
Zero One Knapsack using Dynamic Programming
Zero One Knapsack - Top Down
Zero One Knapsack - Bottom Up
Section 40 - CHALLENGING Dynamic Programming Problems
Longest repeated Subsequence Length problem
Longest Common Subsequence Length problem
Longest Common Subsequence problem
Diff Utility
Shortest Common Subsequence problem
Length of Longest Palindromic Subsequence
Subset Sum Problem
Egg Dropping Puzzle
Maximum Length Chain of Pairs
Section 41 - A Recipe for Problem Solving
Introduction
Step 1 - Understand the problem
Step 2 - Examples
Step 3 - Break it Down
Step 4 - Solve or Simplify
Step 5 - Look Back and Refactor
Section 41 - Wild West
Who this course is for:
- Anybody interested in learning more about data structures and algorithms or the technical interview process!
- Self-taught programmers who have a basic knowledge in Java and want to be professional in Data Structure and Algorithm and begin interviewing in tech positions!
- Students currently studying computer science and want supplementary material on Data Structure and Algorithm and interview preparation for after graduation!
- Professional programmers who need practice for upcoming coding interviews.
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Artificial Intelligence in Video Creation: Supreme Edition
Tuesday, September 28, 2021
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Artificial Intelligence in Video Creation: Supreme Edition - MBA in Creative Arts, Design and Animation: Level 1 - Part 4 Course on Artificial Intelligence in Video Creation
- Highest Rated
- Created by Srinidhi Ranganathan, First Look Digital Marketing Solutions Pvt. Ltd.
- English [Auto]
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What you'll learn
- Learn Biteable - An Amazing Cloud-Based Video Tool for Video Making
- Learn Lumen5 - A spellbinding cloud-based video creation tool to convert article to videos in minutes.
- Learn Content Samurai - Another Artificial Intelligence cloud-based video making tool that delivers automatic voice-over for your video (TTS)
- Learn to create 100's of videos in bulk with the power of automation and Artificial Intelligence (AI) technology
- Know about the top popular Artificial Intelligence Video Creation and Marketing Tools
- Explore the benefits of social media video creation
Description
Welcome to the fourth course as part of the series "MBA in Creative Arts, Design and Animation".
"Artificial Intelligence in Video Creation: Supreme Edition".
This incredible artificial intelligence video creation course 2021 will cover the tools called Biteable and Lumen5 which are the world's simplest video makers offering hundreds of free animated, live-action, or photo scenes in lots of different styles made by top designers.
I will teach you to easily add your own text, photos, colours, and sound to customise your video and edit it all on a simple drag-and-drop timeline.
Once, you've done that we will go through the process of choosing a soundtrack from Biteable's huge, high-quality music library to match the look and feel of your video.
Artificial Intelligence and Its Advancement in Video Creation in 2021 and beyond.
Let's delve down further into the use of AI technology. Artificial Intelligence (AI) is now involved in the creation of smart video and has also been able to influence businesses. Users can now film and edit videos through Artificial Intelligence. It also brings many job opportunities in the field. Due to its ability to sense, reason, act and adapt, AI has suddenly become one of the most important technologies and the most in-demand tool for the video creation market; and also due to the popularity of automation in different business practices. Several companies have invested in keeping video production as their main target in Artificial Intelligence. Examples include AI implementation and deployment through multiple video distribution channels such as Netflix and YouTube. These companies have invested in AI just to make it more exciting and innovative to watch videos. Many aspects of the production and editing process of videos have been handled by artificial intelligence. Its innovation is also a blessing for production teams and video editors. It helps practitioners to concentrate more on creative aspects instead of editing which is perceived by many to be a very dull and repetitive job.
Did you also know this fact?
Most aspects of the production and distribution system are managed by artificial intelligence. It can now record, edit, pick and distribute online videos. Artificial intelligence has allowed automated video editing in 2021. A camera can now operate on its own without human instructions. Ok, so what does this Artificial Intelligence in Video Creation course cover? Let's look into this further. Here is the ultimate question.
Why learn this mind-blowing course and how this can be a differentiator when it comes to AI video creation?
With Biteable, you can convert any plain infographic into fun slides that will not only explain and pass the information but also make the content more understandable. This course can change your life as a video creator.
Biteable is the god of video creation to aid you to create videos in minutes. Lumen5 whereas is an Artificial Intelligence Video Creation Tool that allows you to turn your blog posts, articles into engaging videos to post on social media platforms.
This course will save you tons of time when it comes to creating videos without using any expensive video creation software. The output videos generated will be so powerful that it would create a huge impact on your business. This is highly beneficial to any business and you will realise this inside the course. If you learn how to work on a PowerPoint presentation, you can work on Biteable and Lumen5. An 8th grader can do it.
The question is "Are you ready to get into the video-making action, right now?"
2021 seems to be a great and amazing year to take your video creation efforts to great heights of success.
Who this course is for:
- Video creators, Marketers, Social Media Specialists and anyone who is looking to create videos to promote their brand or business.
- Anyone who is looking to learn the artificial intelligence and automation techniques in Video Creation in 2021
- Passionate students who want to master the concept of Artificial Intelligence (AI) in Video Creation.
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2021 Python for Linear Regression in Machine Learning
2021 Python for Linear Regression in Machine Learning - Linear & Non-Linear Regression, Lasso & Ridge Regression, SHAP, LIME, Yellowbrick, Feature Selection & Outliers Removal
- Created by Laxmi Kant
- English [Auto]
What you'll learn
- Analyse and visualize data using Linear Regression
- Plot the graph of results of Linear Regression to visually analyze the results
- Learn how to interpret and explain machine learning models
- Do in-depth analysis of various forms of Linear and Non-Linear Regression
- Use YellowBrick, SHAP, and LIME to interact with predictions of machine learning models
- Do feature selection and transformations to fine tune machine learning models
- Course contains result oriented algorithms and data explorations techniques
Description
This course teaches you an in-depth analysis of Linear Regression. We cover the theory and coding part together for better understanding. You will learn how to do an exhaustive analysis of machine learning models. We will show you result-oriented techniques to boost the accuracy of your machine learning models. This course teaches you everything you need to create an accurate Linear Regression model in Python.
You should have an introductory knowledge of Python before enrolling in this course otherwise please do not enroll in this course.
After completing this course you will be able to:
Interpret and Explain machine learning models which are treated as a black-box
Create an accurate Linear Regression model in python and visually analyze it
Select the best features for a business problem
Remove outliers and variable transformations for better performance
Confidently solve and explain regression problems
What is covered in this course?
This course teaches you, step by step coding for Linear Regression in Python. The Linear Regression model is one of the widely used in machine learning and it is one the simplest ones, yet there is so much depth that we are going to explore in 14+ hours of videos.
Below are the course contents of this course:
Section 1- Introduction
This section gets you to get started with the setup. Download resources files for code along.
Section 2- Python Crash Course
This section introduces you to the basics of Python programming.
Section 3- Numpy Introduction
This section is optional, you may skip it but I would recommend you to watch it if you are not comfortable with NumPy.
Section 4- Pandas Introduction
This section introduces you to the basic concepts of Pandas. It will help you later in the course to catch up on the coding.
Section 5- Matplotlib Introduction
Do not skip this section. We will be using matplotlib plots extensively in the coming sections. It builds a foundation for a strong visualization of linear regression results.
Section 6- Linear Regression Introduction
We will kick-start our Linear Regression learning. You will learn the basics of linear regression. You will see some examples so that you can understand how Linear Regression works and how to analyze the results.
Section 7- Data Preprocessing for Linear Regression
This section is the most important section. DO NOT SKIP IT. It builds the foundation of data preprocessing for linear regression and other linear machine learning models. You will be learning, what are the techniques which we can use to improve the performance of the model. You will also learn how to check if your data is satisfying the coding of Linear Model Assumptions.
Section 8- Machine Learning Models Interpretability and Explainer
This section teaches you how to open-up any machine learning models. Now you don't need to treat machine learning models as black-box, you will get to learn how to open this box and how to analyze each and every component of machine learning models.
Section 9- Linear Regression Model Optimization
This section extensively uses the knowledge of previous sections so don't skip those. You will learn various techniques to improve model performance. We will show you how to do outliers removal and feature transformations.
Section 10- Feature Selection for Linear Regression
This section teaches you some of the best techniques of feature selection. Feature selection reduces the model complexity and chances of model overfitting. Sometimes the model also gets trained faster but mostly depends on how many features are selected and the types of machine learning models.
Section 11- Ridge & Lasso Regression, ElasticNet, and Nonlinear Regression
This section covers, various types of regression techniques. You will be seeing how to achieve the best accuracy by using the above techniques.
By the end of this course, your confidence will boost in creating and analyzing the Linear Regression model in Python. You'll have a thorough understanding of how to use regression modeling to create predictive models and solve real-world business problems.
How this course will help you?
This course will give you a very solid foundation in machine learning. You will be able to use the concepts of this course in other machine learning models. If you are a business manager or an executive or a student who wants to learn and excel in machine learning, this is the perfect course for you.
What makes us qualified to teach you?
I am a Ph.D. in Machine Learning and taught tens of thousands of students over the years through my classes at IIT and KGP Talkie YouTube channel. Few of my courses are part of Udemy's top 5000 courses collection and curated for Udemy Business. I promise you will not regret it.
Who this course is for:
- Beginners python programmers.
- Beginners Data Science programmers.
- Students of Data Science and Machine Learning.
- Anyone interested in learning Linear Regression and Feature Selection
- Anyone interested about the rapidly expanding world of data science!
- Developers who want to work in analytics and visualization project.
- Anyone who wants to explore and understand data before applying machine learning.
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React - The Complete Guide with React Hook Redux 2021 in 4hr
Monday, September 27, 2021
Free Coupon Discount - Learn how to create high performance web app with react. Hooks, Redux, React Routing, useContext, Fireabase and more | Created by Kim Chen
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- React js. From the beginning. w/ Redux and React Router
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- Complete React Developer in 2020 (w/ Redux, Hooks, GraphQL)
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Description
In this course you will learn to get start with React 16.8+ including what is JSX, how to use props to pass data to the children components, using the React hook useState and also styled component. We will not use more than 40 hours to talking to the same things again and again. You will learn all the react essential things within 4 hours.
Since this course is the mix of knowledge base and the project base. If you just want to learn the React knowledge fast, 4 hours is enough!!
After that we will also provide project to consolidate your understanding with react, and how to interact with backend like Firebase.
Which companies are using React now and why you need to learn?
Netflix
Yahoo! Mail
Dropbox
Atlassian
Salesforce
New York Times.
Cloudflare
Tesla
BBC
GitHub
PayPal
Uber
Zendesk and more...
The above list of big companies taking huge leaps to embrace React, which signifies the extent to which the technology has raised its bars.
What you will learn in this course?
Es6
React components
Jsx
Functional component
Props
State
List
Styled component
Redux
UI framework like Reactstrap, Materializecss
Firebase
Who this course is for:
Anyone who want to start a career with React
Anyone who want to take the web development skills to the next level
Anyone who are interested in learning the most update technology
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Data Structures A-Z : Data Structures + Algorithms Bootcamp
Sunday, September 26, 2021
Free Udemy Coupon
Data Structures A-Z : Data Structures + Algorithms Bootcamp - Become ace in data structures & algorithms & Crack the code interview by getting mastery in data structures & algorithms
- Created by Vinoth Parthasarathy
- English [Auto]
Online Courses Udemy GET COUPON CODE
What you'll learn
- Understand the coding principles and Understand How to write code in efficient way by help of choosing right data structures and efficient algorithms
- How to choose right data structures and right algorithms for your need
- Understand concept behind data structures like Arrays, Linked Lists, Hash tables, Trees, Graph, Stacks, Queues, and Sort algorithms and Search algorithms
- Understand the fundamentals of the Data structures and Algorithms
- Understand popular algorithms, and how to use it when you need.
- Learn everything you need to crack difficult coding interviews.
- Reason about applicability and usability of Data Structures
Description
Congratulations! You've found the most popular, most complete, and most up-to-date resource online for learning Data structures and Algorithms.
Do you want to crack your next coding interview? Do you want to be a master in solving challenging Algorithms?
Are you interested in the field of Data structures? Are you interested to play around with complex Algorithms? Then this course is for you!
You need to understand algorithms and data structures because I've seen code written by people who didn't understand Data structures and algorithms; and trust me, you don't want to be that guy.
The entire course is based around a single goal: Turning you into a professional programmer & capable of writing code as a professional.
Are you scared about the coding interview? Join me in this Adventure, Crack your coding interview by getting mastery in data structures & algorithms.
There are lots of free tutorials and videos on YouTube. Why would you want to take this course? The answer is simple: Quality of teaching. So, from the very beginning to the very end, you'll be confident that you'll be in good hands and watching every minute of the course, unlike reading many free tutorials and videos, do not waste your precious time. Each section is equipped with a balanced mix of theory and Implementation.
It's my goal to make clear Data structures and Algorithms as much as possible and ensure your success. I want everyone to benefit from my courses, that's why we'll dive deeply into Data structures and Algorithms concepts and why I made sure to also share the knowledge that's helpful to programmers
I can promise you that, this is the most comprehensive and modern course you can find on data structures & algorithms on udemy or anywhere else- it's based on all my knowledge And teaching experience. It's both a complete guide, starting with the core basics of the language, as well as an extensive reference of the data structures & algorithms, ensuring that both newcomers, as well as experienced developers, get a lot out of this course! It's my goal to make you clear about the concepts of data structures & algorithms as much as possible. To accomplish this, throughout the course, extensive use of slides and graphics is being utilized in order to aid the understanding and memorability of complex concepts. Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own project. This course is designed to be fast at getting you started but also get you deep into the "why" of things. Simply the fastest and best way to learn the latest skills. Look at the scope of topics in the Session and see the breadth of skills you will learn.
Why it’s the only course you need to learn Data Structures and Algorithms?
This course is everything you need from start to end regardless of your experience.
It's an interactive course. Instead of explaining the concepts with Powerpoint slides, I will take you to the classroom again.
These course videos are designed very carefully to make you more engaging and you won’t get bored while watching the course videos. Unlike other learning videos which you can find on other courses or on YouTube, this course is carefully designed with full of animated content that will make learners grasp the concepts quickly and easily. In this way, you can understand even hard topics/concepts easily.
While you take this course, you will feel the simplicity of learning the language, This is because time spent for preparation for the videos (script for the videos and video structure) and video editing (to cut boring pieces of the lesson or time when the program loads) is huge. And also the structure of the course is created based on beginners in mind. And also this course will be a good reference for those who are already having good knowledge of data structures and algorithms.
Don’t take my word for it. Check the reviews and see what other students are saying
★★★★★
No Words!! The explanation is very simple and clear, And its perfect combination of theory plus practical on Data structure, And I'm simply amazed by the instructor as they make such a hard topic like Data structure very easy to learn.
And it's crisp and straight to the point and examples are really great and the way in which the presenter describes the topic is also very helpful.
Thanks a lot! - Giada
★★★★★
The Concepts are presented in a simpler & detailed way in a short span of time. This is the best course for learning data structures from scratch. Tree part has the best explanation. Sir, you helped me face my fears regarding data structures & coding & have boosted up my confidence. Sir, please post courses on competitive coding Vinoth Sir cause you are the best. - Divyakanti Batabyal
★★★★★
It's a good experience so far, I'm loving the content! I'll give a full review once I'm done. So far I feel it's a very valuable course. Update: After finishing the course I am very happy with it. This is a wonderful course and Vinoth, you have really done an awesome job. Before this course I really don't have much knowledge of Data Structures, this course is designed, which made me really confident about my learning. Thanks a lot, Vinoth. Keep up the great work! - Gayathri
★★★★★
It is evident that Vinoth has put a lot of thought into planning this course. It is well organized and the topics lead nicely into one another. Moreover, Vinoth's teaching experience helps the complex topics to grasp easily. I am really enjoying the course and think Vinoth's teaching style is stellar - Ravi
★★★★★
In a very simple and clear manner, the trainer is explaining things and giving us chance to think and develop our own logic for implementing data structures. It really makes complex things simple !!! I found the videos and code samples very clear and precise. A very good foundation course on data structure -Abhishek Agarwal
★★★★★
the way of teaching is very good, sir is teaching with real-time examples which helps us to easily understand the topic. Sir made this course very easy for me to understand, such a great teacher - Aditya Bohra
★★★★★
This course is a good match for me, Till start, to end its well-executed, Content and syllabus is good, for me as a beginner is very useful, i learnt lots of thing from this course, Thank you very much for such a wonderful course. thanks - Magnus
★★★★★
Explained clearly, This course covers all the basics and beyond. I learnt what I want to learn plus much more. Vinoth explains clearly, I enjoyed the way he taught, very precisely and briefly. Honestly, the course is good for beginners - Noel
★★★★★
I found this course is much valuable for me, especially Tree and Graph sections are awesome, Neat presentation, easily understandable course, overall its must have taken the course who what to understand data structures and algorithms from the base. Thanks - Abinav
★★★★★
Incredibly comprehensive course! I found this course really well laid out and easy to get to grips with, concepts were introduced in a very logical manner which made it easy to follow. Overall this course matched my expectations and expanding my current knowledge of data structures. Thanks - Trinity
★★★★★
Super Good! The teaching style, content and quality of the course all are excellent. Over this is the perfect material for data structures and algorithms. I will highly recommend this course to my friends. Thanks a lot for such a wonderful course. - Celia
Why you should learn Data Structures and Algorithms:
Industry Demand for Data Structures and Algorithms: Top tier tech brands such as Google, Facebook, Microsoft, Youtube, etc. focus more on designing things in the most optimal manner that improves user experience and enhances tracking and managing. These companies ask most of the questions related to Data Structures and Algorithms in interviews to assess a candidate's approach for solving any real-world problem.
Solve the problem more efficiently: The search engine may provide source code for solving the issue or steps for you to fix the issue. But, the real programmer understands the Application Programming Interface internals including data structure and make the decision.
Improving problem-solving and analytical skills: Data Structures and Algorithms are not only crucial to land your dream job, but it also helps in improving problem-solving and analytical skills that can prompt you to think out-of-the-box solutions.
Use the Right tool to solve the problem: The data structure and algorithm provide a set of techniques to the programmer for handling the data efficiently. The programmer should understand the core concepts of data handling the data. Data structure and algorithms help you to decide the right tool for your job
Furthermore, it will also enable your future endeavours as it is something that will never go out of demand considering the rapid evolution of technologies and an increasing amount of data.
Here’s just some of what you’ll learn
(It’s okay if you don’t understand all this yet, you will in the course)
This course is fun and exciting, but at the same time, we dive deep into Data Structures and Algorithms. Specifically, you will learn :
· Understanding the core principles of coding.
· Understanding code complexity and how to write code efficiently and various levels of complexity.
· Basics of Data Structures and algorithms
· Basic data structures (Arrays, linked list, and Hash Table)
· Tree data structures
· Graph data structures
· Algorithms to apply Graph in product implementation
· Searching algorithms
· Various Sorting algorithms
Frequently Asked Questions:
Will I be able to learn Data Structures and Algorithms and find a job after completing this course?
YES, This course covers all the topics in a very detailed way which you need to know to become a professional Data Structures and Algorithms. However, you will be able to learn Data Structures and Algorithms and be job-ready heavily depends on you once you completed this course.
If you merely watch the videos, you will hardly learn anything without trying things on your computer. Instead, try the code on your computer, change the code, run it, improve it further, rerun it, fix the possible errors, try making a similar app, repeat, ask questions in the Q&A when you get stuck, and try to solve all the exercises in the course. That way, you will undoubtedly learn how to use Data Structures and Algorithms and find a job.
How much time will I need to complete the course?
That depends on how much effort you can put into learning the language. If you dedicatedly follow the course, you can complete the course in 1 week. And If you practice the programs in day to day life, You will be getting familiar with the Data Structures and Algorithms in a very short period.
I don't know anything about programming. Will I still be able to learn Data Structures and Algorithms?
Absolutely YES. This course assumes you have no previous knowledge of any programming.
Do I need to have any prior knowledge to take this course?
A big NO. You don’t need any prior knowledge to take this course. I have designed this course which makes it comfortable even for beginners. It starts from the absolute beginner level initially and gradually moving to complex and advanced level topics. And also this course is filled up full of practical and fun examples. You will learn the core skills step by step with hands-on experience. And If you are already comfortable with coding and need to refresher your skill, this course will be suitable for you, too. Every time you come back to this course you will learn something new or improve yourself.
Does the course expire?
No. Once you buy the course, it's yours. I update the content regularly, and all the updates come to you for free in the one-time purchase you make.
Will I get support if I get stuck?
Yes. Feel free to drop a question in the Q&A, and I will answer your questions within the same day. I covered almost everything that you need to become expert in Data Structures and Algorithms. if you feel, this course wasn’t complete enough, I offer full support, answering any questions you have 7 days a week.
What if I have questions?
As if this course wasn’t complete enough, I offer full support, answering any questions you have 7 days a week.
What’s stopping you from signing up today?
You don’t have enough time? Not an issue. I’ve designed this course so you can learn everything you need in as little as ONE week.
You’re still weighing up the value? Listen. I’ve made this course bigger, better and more affordable—with even more content and more coding tips and best practices —than EVER before. And In this course, I show you how to create all of the code from scratch. You can type the code along with me in the videos, which is the best way to learn. And I am a very responsive instructor and I am available to answer your questions and help you work through any problems.
You don’t have any previous experience? Seriously, not a problem. This course is expertly designed to teach everyone from complete beginners, right through to pro developers. (And yes, even pro developers take this course to quickly absorb the latest skills, while refreshing existing ones).
Straight up: There's no other course that teaches you that, so join thousands of other students who have successfully applied their data structures and algorithms in the real world. Sign up and start learning the expert in data structures and algorithms today!
Sounds great, doesn’t it? Are you ready for a life-changing adventure? If you are serious about your career as a software developer, this is the only Bootcamp you will need. Then don't waste your time with random tutorials or incomplete youtube videos. This course is an easy-to-follow, all-in-one packages that will take your skills to the next level.
Buy this course today, and you will get all updates for FREE!
Enroll now and begin your journey towards the most lucrative, adventurous and exciting career path you can imagine! Or, take this course for a free spin using the preview feature, so you know you’re 100% certain this course is for you.
100% MONEY-BACK GUARANTEE
This course comes with a 30-day full money-back guarantee. Take the course, go through the lectures, do the exercises, and if you're not happy, ask for a refund within 30 days. All your money back every last penny questions asked.
You either end up with an expert in Data Structures and algorithms skills, go on to develop great programs and potentially make an awesome career for yourself, or you try the course and simply get all your money back if you don’t like it… (And why not give such a guarantee? I certain this course will provide a ton of value for you)
You literally can’t lose.
See you on the inside (hurry, Data structures, and algorithm class is waiting!)
Who this course is for:
- Anyone who want to take their programming skills to the next level and learn a future-proof programming
- Anyone who want to become intelligent programmer
- Anyone who is Feeling scared about coding interview
- Anyone who wants to strengthen their problem-solving skills
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Python for Beginners: Learn Python Hands-on (Python 3)
Python for Beginners: Learn Python Hands-on (Python 3) - Python 101: Easiest Python for Beginners course to harness the power of Python and make you love Python. (In Python 3)
- Created by TechnoBytes | Take Learning to Byte Level
- English [Auto]
Students also bought
- 2020 Complete Python Bootcamp From Zero to Hero in Python
- Machine Learning A-Z™: Hands-On Python & R In Data Science
- Python for Data Science and Machine Learning Bootcamp
- Learn Python Programming Masterclass
Description
Whether you want to learn Python because:
· You are a rookie and want to learn programming.
· You are an existing programmer and want to learn Python from scratch.
· Enhance your programming fundamentals.
· Apply for Python related jobs.
· Get started with Machine Learning, Data Science, Django or other hot areas that Python specializes in
Then congratulations! You have come to the right place. This course has been designed to teach you Python from scratch and raise your status from a beginner python programmer to an intermediate level programmer.
Why learn Python?
Over the last few years, Python’s popularity has increased tremendously. Demand for Python programmers and developers is increasing in the industry and it is a prerequisite that can help you enter some of the most exciting and trending fields, including data science, machine learning, artificial intelligence, web applications, IOT and many more. Python is easily one of the "most loved” and “most wanted” programming languages. This course will help you stay ahead in the ever growing race of career opportunities.
What will I learn in this course?
· Importance of Python in today’s technological world.
· All the core programming fundamentals - keywords, identifiers, variables, and much more.
· Python Operators
· Flow of control – Conditional statements, looping statements and jump statements with a number of examples explained line by line.
· In depth working of Functions, Parameters, Scope and lifetime of variables.
· Primitive data types of Python.
· Python Data Structures – Strings, Lists, Tuples, Dictionaries and Sets in complete detail.
· File Handling – What are files? Why are files needed? How to create files and perform read, write operations and much more.
· Directory Management using Python
· Mini Gaming Project to help apply all the concepts learnt and boost your confidence level.
Why this course?
· Practical and project-based learning is one of the most effective way to learn programming.
· If you hate theory, but love practical work, then this course is meant for you. This is not simply a tutorial. The content of the course is a mixture of practical video lectures, quizzes, assignments, and project to help you become a professional Python programmer.
· No need to go through various YouTube tutorials, boring textbooks, stack flow posts to understand small details. The lectures cover every minute detail with every line of code explained.
· Awesome Quality Content: Over 10+ hours of HD Videos.
· The content is Well Structured & Easy To Learn.
· Quizzes and Assignments after every section have been designed for you to check your understanding.
· High quality help and support.
· Start at zero and become an expert
What if you have questions?
We offer full support and are ready to answer your questions 7 days a week. There is no need for you to worry about getting stuck in some topic and not being able to proceed forward. Anytime, anywhere, Team Technobytes is always there to help you and guide you.
No Risk Involved
You either end up with great Python Programming skills and a mini-project on your resume or with money-back guarantee.
You literally can’t lose.
Who this course is for?
· Rookies with no previous programming experience and want to learn programming.
· Anyone who wants to gain knowledge of core programming concepts as a pre-requisite for moving into machine learning, data science, and artificial intelligence.
· Anyone who wants to learn Python for career-related purpose.
· Existing programmers who want to learn Python.
· If you are an expert Python programmer then this course is probably not for you.
· This course does not delve into the topics of machine learning, artificial intelligence or object oriented programming.
React JS: Learn React JS From Scratch with Hands-On Projects
Friday, September 24, 2021
Free Coupon Discount - React JS: Learn React JS From Scratch with Hands-On Projects, This is the best way to learn React JS. Start learning from scratch, dive in React JS and become React Developer | Created by Oak Academy
Preview this Udemy Course GET COUPON CODE
Description
Hello there,
Welcome to React JS: Learn React JS From Scratch with Hands-On Projects course.
React is one of the best choices for building modern web applications. If you are new to React or maybe you've been struggling to learn and truly understand what’s going on then this course is the best way for you to learn React JS.
In this course, we will take you through everything you need to know to master web development using ReactJS by providing a powerfull knowledge through a mixture of diagrams and the creation of a simple application.
No Previous Knowledge is needed!
You don’t need to have previous knowledge about React. This course will take you from a beginner to a more advanced level with hands-on examples.
You will be confident in using React JS, and if you ever get stuck, we will be there to help.
Learn by doing!
So we have made this course as simple as possible in order to take you through step by step so you can feel confident and get a truly good understanding of how to utilize ReactJS. In this course, we will be teaching React by creating various projects.
Here is the list of what you’ll learn by the end of course,
We will start with local installation and react basics. After that, we will create 5 projects.
Project 1 – Learn, create react app and Jsx with ‘first-app’
Project 2 – Learn React props system with ‘blog-posts’ app
Project 3 – Learn react components, state, lifecycle methods, async operations and much more... with ‘hemisphere’ app
Project 4 – Handling event handlers, fetching data from an outside api and showing list of records with ‘image-list’ app
Project 5 - Routing with React Router and using React Portals to render children outside the DOM hierarchy with ‘react-router’ app
At the end of the course
By the end of the course, you will be able to build amazing React single page web applications.
Fresh Content
It’s no secret how technology is advancing at a rapid rate. New tools are released every day, and it’s crucial to stay on top of the latest knowledge for being a better React developer. You will always have up-to-date content for this course at no extra charge.
Video and Audio Production Quality
All our content is created/produced as high-quality video/audio to provide you the best learning experience.
You will be,
Seeing clearly
Hearing clearly
Moving through the course without distractions
You'll also get:
✔ Lifetime Access to The Course
✔ Fast & Friendly Support in the Q&A section
✔ Udemy Certificate of Completion Ready for Download
Dive in now!
We offer full support, answering any questions.
See you in the class!
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2021 Data Science/MachineLearning Project Deployment Mastery
Free Udemy Coupon
2021 Data Science/MachineLearning Project Deployment Mastery - Learn Data Science/ML with 20+Practical Hands-On Projects and Deployment.(Flask,Heroku,AWS,Google Cloud,Microsoft Azure)
- Created by MrBriit ., Bright kyeremeh
- English [Auto]
Online Courses Udemy GET COUPON CODE
What you'll learn
- End-to-End Data Science and Machine Learning (Right from learning the basics to building the models to deploying the models)
- Learn Through More Than 20+ Projects and Assignments
- Master Machine Learning With Python
- Learn How to Deploy Machine Learning Models
- Practical Hands-On Data Science Projects Mastery
- Build And Deploy Machine Learning models On Flask, Heroku, Streamlit, AWS,Google Cloud, Microsoft Azure
- Create Robust Machine Learning Models with CatBoost ,XGBoost, LightGbm
- Learn Different Machine Learning Algorithms such as Linear And Logistic regression, Naive Bayes,KNN,SVM,K-means, etc.
- Deal With Data Imbalance (Upsampling/Downsampling/SMOTE)
- Beginner To Advance
- Gain Confidence In Performing Exploratory Data Analysis (EDA)
- Choose The Right Machine Learning Model For Your Problem Statement
- Access To Exclusive Community To Learn With Others And Answer Your Queries
- Learn The Necessary Statistics
- Master Data Analysis
Description
Interested in the field of Data Science and Machine Learning?
Interested in Building Data Science and Machine Learning Projects and Deploy on Platforms such as AWS, Google Cloud, Microsoft Azure, Heroku, Flask, Streamlit?
Interested in learning it the practical way?
Then this course is for you!!
This course has been practically and carefully designed by industry experts to offer the best way of learning Data Science and Machine Learning the practical way with hands-on projects and Deployment throughout the course.
This course will help you learn complex Data Science concepts and machine learning algorithms the practical way for easier understanding.
We will walk you through step-by-step on each topic explaining each line of code for your understanding.
There is going to be a lot of fun, excited, and robust projects to better understand each concept under each topic.
We have structured the course in this way:
Python For Data Science
Statistics For Data Science
Machine Learning
Hands-on projects on each topic
Projects Deployment Tutorial
Streamlit project tutorial
Flask deployment project tutorial
Heroku deployment project tutorial
Google cloud deployment project tutorial
AWS deployment project tutorial
Microsoft Azure deployment project tutorial
This course aims to help beginners, as well as intermediate data science enthusiasts, learn both the concepts while practicing on the projects to gain a better understanding of the course.
Who this course is for:
- Anyone interested in Data Science and Machine Learning.
- Anyone who wants to Build And Deploy machine learning models on Flask, Heroku, AWS,Google Cloud, Microsoft Azure, Streamlit
- Any student interested in a career in Data Science and Machine Learning
- Any beginner level interested to kick-start their career in Data Science and Machine Learning
- Any intermediate level learner who know the basics of python, statistics, machine Learning and want to learn more about it
- Anyone not that comfortable with coding but interested in Data Science and Machine Learning and want to easily understand the concepts
- Any data analysts who want to transition to Data Science and Machine Learning
- Any Business Analysts who want to transition to Data Science and Machine Learning
- Anyone not satisfied with their job and looking for a career transition to become a Data Scientist.
- Anyone who wants to leverage the power of data in his case scenario.
- Any curious mind
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Machine Learning in Python with 5 Machine Learning Projects
Thursday, September 23, 2021
Machine Learning in Python with 5 Machine Learning Projects - Learn Complete Machine Learning Bootcamp with Python. Build 5 Complete Machine Learning Real World Projects with Python.
- Hot & New
- Created by Data is Good
- English [Auto]
What you'll learn
- Theory and practical implementation of linear regression using sklearn
- Theory and practical implementation of logistic regression using sklearn
- Feature selection using RFECV
- Data transformation with linear and logistic regression.
- Evaluation metrics to analyze the performance of models
- Industry relevance of linear and logistic regression
- Mathematics behind KNN, SVM and Naive Bayes algorithms
- Implementation of KNN, SVM and Naive Bayes using sklearn
- Attribute selection methods- Gini Index and Entropy
- Mathematics behind Decision trees and random forest
- Boosting algorithms:- Adaboost, Gradient Boosting and XgBoost
- Different Algorithms for Clustering
- Different methods to deal with imbalanced data
- Correlation Filtering
- Variance Filtering
- PCA & LDA
- Content and Collaborative based filtering
- Singular Value Decomposition
- Different algorithms used for Time Series forecasting
- Case studies
Description
Crazy about Data Science and Machine Learning?
This course is a perfect fit for you.
This course will take you step by step into the world of Machine Learning.
Machine Learning is the study of computer algorithms that automates analytical model building. It is a branch of Artificial Intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
Machine Learning is actively being used today, perhaps in many more places than one world expects.
It contains a lot of topics and this course will cover all step by step.
This Machine Learning course will give you theoretical as well as practical knowledge of Machine Learning.
This Machine Learning course is fun as well as exciting.
It will cover all common and important algorithms and will give you the experience of working on some real-world projects.
This course will cover the following topics:-
1. Theory and practical implementation of linear regression using sklearn.
2. Theory and practical implementation of logistic regression using sklearn.
3. Feature selection using RFECV.
4. Data transformation with linear and logistic regression.
5. Evaluation metrics to analyze the performance of models
6. Industry relevance of linear and logistic regression.
7. Mathematics behind KNN, SVM, and Naive Bayes algorithms.
8. Implementation of KNN, SVM, and Naive Bayes using sklearn.
9. Attribute selection methods- Gini Index and Entropy.
10. Mathematics behind Decision trees and random forest.
11. Boosting algorithms:- Adaboost, Gradient Boosting, and XgBoost.
12. Different algorithms for clustering
13. Different methods to deal with imbalanced data.
14. Correlation filtering
15. Variance filtering
16. PCA & LDA
17. Content and Collaborative based filtering
18. Singular Value decomposition
19. Different algorithms used for Time Series forecasting.
20. Case studies
We have covered each and every topic in detail and also learned to apply them to real-world problems.
There are lots and lots of exercises for you to practice and also a 5 bonus Python Machine Learning Project "Employee Promotion Prediction", "Predicting Medical Health Expenses", "Determining Status for Loan Applicants" and "Optimizing Crop Production".
In this Python Machine Learning Employee Promotion Prediction project, you will learn how to Implement a Predictive Model for Identifying the Right Employees deserving of Promotion. Also, learn how to balance Imbalanced Datasets.
In this Python Machine Learning Predicting Medical Health Expenses project, you will learn how to Implement a Regression Analysis Predictive Model for Predicting the Future Medical Expenses for People using Linear Regression, Random Forest, Gradient Boosting, etc.
In this Python Machine Learning Determining Status for Loan Applicants project, you will learn how to Implement a Classification Analysis Predictive Model for Determining whether a Person should be Granted a Loan or Not.
In this Python Machine Learning Optimizing Crop Production project, you will learn about Precision Farming using Data Science Technologies such as Clustering Analysis and Classification Analysis. You will be able to Recommend the best Crops to Farmers to Increase their Productivity.
You will make use of all the topics read in this course.
You will also have access to all the resources used in this course.
Enroll now and become a master in machine learning.
Who this course is for:
Anyone who want to start a career in Machine Learning.
Students who have at least knowledge in linear algebra, calculus, statistics, probability and who want to start their journey in Machine Learning.
Any people who want to level up their Machine Learning Knowledge.
Software developers or programmers or Tech lover who want to change their career path to machine learning.
Technologists who are curious about how Machine Learning works in the real world.
Anyone who has already started their data science journey and now want to master in machine learning.
If you have no prior coding or scripting experience, This course is completely for you. This Course also includes Python Fundamental for beginners.
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React: Learn React JS From Scratch with Hands-On Projects
Wednesday, September 22, 2021
Online Courses Udemy - React: Learn React JS From Scratch with Hands-On Projects, This is the best way to learn React JS. Start learning from scratch, dive in React JS and become React Developer
NEW, Created by Oak Academy, English
PREVIEW THIS COURSE - GET COUPON CODE
What you'll learn
- Learn React JS
- This course is the best way to learn React JS
- Dive in React JS
- Become React Developer
- Learn how to build single page applications with React JS
- Learn components, props, states and component life cycle methods in React JS
- Create reusable React Components
- Learn modern JavaScript, ES6
- Learn to connect to an external API
- User Inputs, Forms and Events in React
- Routing with React Router
- Using React Portals to render Children Outside the DOM Hierarchy
Requirements
- No prior knowledge is required!
- A Windows PC, Mac or Linux Computer
- JavaScript + HTML + CSS fundamentals are absolutely required but you don’t need to be an expert
- Es6 knowledge would be beneficial but not required
- Desire to learn React
- Nothing else! It’s just you, your computer and your ambition to get started today
Description
Hello there,
Welcome to React: Learn React JS From Scratch with Hands-On Projects course.
React is one of the best choices for building modern web applications. If you are new to React or maybe you've been struggling to learn and truly understand what’s going on then this course is the best way for you to learn React JS.
In this course, we will take you through everything you need to know to master web development using ReactJS by providing a powerfull knowledge through a mixture of diagrams and the creation of a simple application.
No Previous Knowledge is needed!
You don’t need to have previous knowledge about React. This course will take you from a beginner to a more advanced level with hands-on examples.
You will be confident in using React JS, and if you ever get stuck, we will be there to help.
Learn by doing!
So we have made this course as simple as possible in order to take you through step by step so you can feel confident and get a truly good understanding of how to utilize ReactJS. In this course, we will be teaching React by creating various projects.
Here is the list of what you’ll learn by the end of course,
We will start with local installation and react basics. After that, we will create 5 projects.
Project 1 – Learn, create react app and Jsx with ‘first-app’
Project 2 – Learn React props system with ‘blog-posts’ app
Project 3 – Learn react components, state, lifecycle methods, async operations and much more... with ‘hemisphere’ app
Project 4 – Handling event handlers, fetching data from an outside api and showing list of records with ‘image-list’ app
Project 5 - Routing with React Router and using React Portals to render children outside the DOM hierarchy with ‘react-router’ app
At the end of the course
By the end of the course, you will be able to build amazing React single page web applications.
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It’s no secret how technology is advancing at a rapid rate. New tools are released every day, and it’s crucial to stay on top of the latest knowledge for being a better security specialist. You will always have up-to-date content for this course at no extra charge.
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✔ Udemy Certificate of Completion Ready for Download
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Mathematical Foundations of Machine Learning
Mathematical Foundations of Machine Learning - Essential Linear Algebra and Calculus Hands-On in NumPy, TensorFlow, and PyTorch
- Created by Dr Jon Krohn, Ligency Team
- English [Auto]
What you'll learn
- Understand the fundamentals of linear algebra, a critical subject underlying all ML algorithms and data science models
- Manipulate tensors using all three of the most important Python tensor libraries: NumPy, TensorFlow, and PyTorch
- How to apply all of the essential vector and matrix operations for machine learning and data science
- Reduce the dimensionality of complex data to the most informative elements with eigenvectors, SVD, and PCA
- Solve for unknowns with both simple techniques (e.g., elimination) and advanced techniques (e.g., pseudoinversion)
- Be able to more intimately grasp the details of cutting-edge machine learning papers
Description
To be a good data scientist, you need to know how to use data science and machine learning libraries and algorithms, such as Scikit-learn, TensorFlow, and PyTorch, to solve whatever problem you have at hand.
To be an excellent data scientist, you need to know how those libraries and algorithms work under the hood. This is where our Mathematical Foundations of Machine Learning comes in.
Led by deep learning guru Dr. Jon Krohn, this course provides a firm grasp of the mathematics, such as linear algebra and calculus, that underlies machine learning algorithms and data science models.
The course is broken down into the following sections:
Linear Algebra Data Structures
Tensor Operations
Matrix Properties
Eigenvectors and Eigenvalues
Matrix Operations for Machine Learning
Limits
We have finished filming additional content on calculus (Sections 7 through 10), which will be edited and uploaded in Spring 2021. At that point, the Mathematical Foundations of Machine Learning course could be considered complete, but we will continue adding bonus content — on probability, statistics, data structures, and optimization — as quickly as we can. Enrollment now includes free, unlimited access to all of this future course content — over 25 hours in total.
Throughout each of the sections, you'll find plenty of hands-on assignments, Python code demos, and practical exercises to get your math game up to speed!
Are you ready to become an outstanding data scientist? See you in the classroom.
Who this course is for:
You use high-level software libraries (e.g., scikit-learn, Keras, TensorFlow) to train or deploy machine learning algorithms, and would now like to understand the fundamentals underlying the abstractions, enabling you to expand your capabilities
You’re a software developer who would like to develop a firm foundation for the deployment of machine learning algorithms into production systems
You’re a data scientist who would like to reinforce your understanding of the subjects at the core of your professional discipline
You’re a data analyst or A.I. enthusiast who would like to become a data scientist or data/ML engineer, and so you’re keen to deeply understand the field you’re entering from the ground up (very wise of you!)
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