Deep Learning for Beginner (AI) - Data Science
Deep Learning for Beginner (AI) - Data Science - Deep Learning for beginner, Mathematical & Graphical explanation of deep learning with ebooks and Python projects
New | Created by Moein Ud Din
Learn Deep Learning from scratch. It is the extension of a Machine Learning, this course is for beginner who wants to learn the fundamental of deep learning and artificial intelligence. The course includes video explanation with introductions (basics), detailed theory and graphical explanations. Some daily life projects have been solved by using Python programming. Downloadable files of ebooks and Python codes have been attached to all the sections. The lectures are appealing, fancy and fast. They take less time to walk you through the whole content. Each and every topic has been taught extensively in depth to cover all the possible areas to understand the concept in most possible easy way. It's highly recommended for the students who don’t know the fundamental of machine learning studying at college and university level.
What you'll learn
- Introduction to Deep learning, resemblance of artificial neural network and biological neural network
- Activation function and its types, Application of activation function, Linear activation function, Non-linear activation function
- Types of activation function: Step function, Sign function, Linear function, ReLU function, Leaky ReLU function, Tangent Hyperbolic function, Sigmoid, Softmax
- Artificial neural network, ANN model, Complex ANN model, Labelled ANN model, Forward ANN, Backward ANN, ANN python project
- Convolutional Neural Network (CNN), CNN block diagram, Filter or Kernel, Types of filters, Stride, Padding, Pooling, Flatten, CNN Python project
- Recurrent Neural Network (RNN), RNN model, Operation of RNN model, Types; One-one RNN model, One-many RNN model, Many-many RNN model
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