Grokking deep learning / Andrew W. Trask.

Includes index.

Introducing deep learning : why you should learn it -- Fundamental concepts : how do machines learn? -- Introduction to neural prediction : forward propagation -- Introduction to neural learning : gradient descent -- Learning multiple weights at a time : generalizing gradient descent -- Building your first deep neural network : introduction to backpropagation -- How to picture neural networks : in your head and on paper -- Learning signal and ignoring noise : introduction to regularization and batching -- Modeling probabilities and nonlinearities : activation functions -- Neural learning about edges and corners : intro to convolutional neural networks -- Neural networks that understand language : king - man + woman ==? -- Neural networks that write like Shakespeare : recurrent layers for variable-length data -- Introducing automatic optimization : let's build a deep learning framework -- Learning to write like Shakespeare : long short-term memory -- Deep learning on unseen data : introducing federated learning -- Where to go from here : a brief guide.