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
How to Enroll Deep Learning for Beginner (AI) – Data Science course?
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