An Introduction to Deep Learning

An Introduction to Deep Learning is the complete guide to writing deep learning programs with the widely-used Python language and TensorFlow programming environment.

Building on his pioneering undergraduate and graduate courses, Brown University professor Eugene Charniak covers every key concept and technique, including feed-forward neural nets, convolutional neural nets, word embeddings, recurrent neural nets, sequence-to-sequence learning, deep reinforcement learning, unsupervised models, and more. Each chapter contains a full programming project and a set of exercises carefully crafted to help readers build mastery, as well as additional readings and references for even deeper insight.

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.