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.

"Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare!"-- Publisher's description.