Introduction to Deep Learning

This book PDF is perfect for those who love Computers genre, written by Eugene Charniak and published by MIT Press which was released on 29 January 2019 with total hardcover pages 187. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Introduction to Deep Learning books below.

Introduction to Deep Learning
Author : Eugene Charniak
File Size : 55,5 Mb
Publisher : MIT Press
Language : English
Release Date : 29 January 2019
ISBN : 9780262039512
Pages : 187 pages
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Introduction to Deep Learning by Eugene Charniak Book PDF Summary

A project-based guide to the basics of deep learning. This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning. The author, a longtime artificial intelligence researcher specializing in natural-language processing, covers feed-forward neural nets, convolutional neural nets, word embeddings, recurrent neural nets, sequence-to-sequence learning, deep reinforcement learning, unsupervised models, and other fundamental concepts and techniques. Students and practitioners learn the basics of deep learning by working through programs in Tensorflow, an open-source machine learning framework. “I find I learn computer science material best by sitting down and writing programs,” the author writes, and the book reflects this approach. Each chapter includes a programming project, exercises, and references for further reading. An early chapter is devoted to Tensorflow and its interface with Python, the widely used programming language. Familiarity with linear algebra, multivariate calculus, and probability and statistics is required, as is a rudimentary knowledge of programming in Python. The book can be used in both undergraduate and graduate courses; practitioners will find it an essential reference.

Introduction to Deep Learning

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