The amateur’s guide to explore Deep Learning# Math Architecture Symbols & Naming Conventions Flow Shapes Dense Layer Forward Backward Model Activation Functions Sigmoid Stepwise Relu Leaky Relu Softplus Hyperbolic Tangent(Tanh) Softmax Gaussian Loss Categorical Cross Entropy Optimization Algortihms Gradient Descent Mini Batch Gradient Descent What is log Intuition Regression Intuition Fitting a linear regression model lets try something with Neural Networks lets try with a little bit complex pattern sine wave with a nerual network Classification Intuition Basic Classification Easy Spiral Classification Complex Spiral Classification Types Recurrent Neural Network References What is it? Load data How the data looks like Data Preparation Simple RNN Basic AutoEncoders Architecture Kohonen Self-Organizing Maps References Intro Other Docs https://mlguidebook.com https://nlp.mlguidebook.com https://reco.mlguidebook.com Indices and tables# Index Module Index Search Page