Deep Learning for Beginner (AI) – Data Science

1. Introduction to Deep learning, resemblance of artificial neural network and biological neural network
2. Activation function and its types, Application of activation function, Linear activation function, Non-linear activation function
3. Types of activation function: Step function, Sign function, Linear function, ReLU function, Leaky ReLU function, Tangent Hyperbolic function, Sigmoid, Softmax
4. Artificial neural network, ANN model, Complex ANN model, Labelled ANN model, Forward ANN, Backward ANN, ANN python project
5. Convolutional Neural Network (CNN), CNN block diagram, Filter or Kernel, Types of filters, Stride, Padding, Pooling, Flatten, CNN Python project
6. Recurrent Neural Network (RNN), RNN model, Operation of RNN model, Types; One-one RNN model, One-many RNN model, Many-many RNN model