Daniel P. Friedman and I (Anurag Mendhekar) are pleased to announce that our upcoming book The Little Learner: A Straight Line to Deep Learning just got its release date, complete with a Preorder Sale (Barnes and Noble, 25%) The book comes out on 2/21/2023.

"The Little Learner" covers all the concepts necessary to develop an intuitive understanding of the workings of deep neural networks: tensors, extended operators, gradient descent algorithms, artificial neurons, dense networks, convolutional networks, residual networks and automatic differentiation.

The authors aim to explain the workings of Deep Learning to readers who may not have the mathematical sophistication necessary to read the existing literature on the subject. Unlike other books in the field, this book makes very few assumptions about background knowledge (high-school mathematics and familiarity with programming). The authors use a layered approach to construct advanced concepts from first principles using really small (“little”) programs that build on one another. This is one of the things that makes this book unique.

The other is that it introduces these ideas using a conversational style in Question/Answer format that is characteristic of the other books in the Little series. The conversational style puts the reader at ease and enables the introduction of ideas in frame-by-frame manner as opposed to being hit with a wall of text.

It is (of course!) written using elementary Scheme and the code will be released as a Racket package.