Introduction to Deep Learning (MIT Press)
Monday, 11 February 2019

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. Author Eugene Charniak, 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. The book illustrates the basics of deep learning by working through programs in the Tensorflow open-source machine learning framework

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Author: Eugene Charniak
Publisher: MIT Press
Date: January 2019
Pages: 192
ISBN: 978-0262039512
Print: 0262039516
Audience: Developers wanting to learn deep learning
Level: Intermediate
Category: Artificial Intelligence

 

introdeep

 

 

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Beautiful C++

Author: J. Guy Davidson and Kate Gregory
Publisher: Addison-Wesley Professional
Date: December 2021
Pages: 352
ISBN: 978-0137647842
Print: 0137647840
Kindle: B09HTH1X38
Audience: C++ developers
Rating: 5
Reviewer: Mike James
Can C++ be beautiful?



Android Programming: The Big Nerd Ranch Guide (5e)

Authors: Bryan Sills, Brian Gardner, Brian Hardy and Kristin Marsicano
Publisher: Addison-Wesley
Pages: 688
ISBN: 978-0137645541
Print: 0137645546
Kindle: B09WLF84W7
Audience: Kotlin programmers
Rating: 4.5
Reviewer: Mike James  

The Big Nerd Ranch Guide to Android is bac [ ... ]


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