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Deep Learning Quick Reference

Deep Learning Quick Reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

By Mike Bernico
$35.99 $24.99
Book Mar 2018 272 pages 1st Edition
eBook
$35.99 $24.99
Print
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eBook
$35.99 $24.99
Print
$43.99
Subscription
$15.99 Monthly

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Product Details


Publication date : Mar 9, 2018
Length 272 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781788837996
Vendor :
Google
Category :
Languages :
Concepts :
toc View table of contents toc Preview Book toc Download Code

Key benefits

  • A quick reference to all important deep learning concepts and their implementations
  • Essential tips, tricks, and hacks to train a variety of deep learning models such as CNNs, RNNs, LSTMs, and more
  • Supplemented with essential mathematics and theory, every chapter provides best practices and safe choices for training and fine-tuning your models in Keras and Tensorflow.

Description

Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It moves deep learning from academia to the real world through practical examples. You will learn how Tensor Board is used to monitor the training of deep neural networks and solve binary classification problems using deep learning. Readers will then learn to optimize hyperparameters in their deep learning models. The book then takes the readers through the practical implementation of training CNN's, RNN's, and LSTM's with word embeddings and seq2seq models from scratch. Later the book explores advanced topics such as Deep Q Network to solve an autonomous agent problem and how to use two adversarial networks to generate artificial images that appear real. For implementation purposes, we look at popular Python-based deep learning frameworks such as Keras and Tensorflow, Each chapter provides best practices and safe choices to help readers make the right decision while training deep neural networks. By the end of this book, you will be able to solve real-world problems quickly with deep neural networks.

What you will learn

[*] Solve regression and classification challenges with TensorFlow and Keras [*] Learn to use Tensor Board for monitoring neural networks and its training [*] Optimize hyperparameters and safe choices/best practices [*] Build CNN s, RNN s, and LSTM s and using word embedding from scratch [*] Build and train seq2seq models for machine translation and chat applications. [*] Understanding Deep Q networks and how to use one to solve an autonomous agent problem. [*] Explore Deep Q Network and address autonomous agent challenges.

What do you get with eBook?

Feature icon Instant access to your Digital eBook purchase
Feature icon Download this book in EPUB and PDF formats
Feature icon Access this title in our online reader with advanced features
Feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details


Publication date : Mar 9, 2018
Length 272 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781788837996
Vendor :
Google
Category :
Languages :
Concepts :

Table of Contents

15 Chapters
Preface Packt Packt
The Building Blocks of Deep Learning Packt Packt
Using Deep Learning to Solve Regression Problems Packt Packt
Monitoring Network Training Using TensorBoard Packt Packt
Using Deep Learning to Solve Binary Classification Problems Packt Packt
Using Keras to Solve Multiclass Classification Problems Packt Packt
Hyperparameter Optimization Packt Packt
Training a CNN from Scratch Packt Packt
Transfer Learning with Pretrained CNNs Packt Packt
Training an RNN from scratch Packt Packt
Training LSTMs with Word Embeddings from Scratch Packt Packt
Training Seq2Seq Models Packt Packt
Using Deep Reinforcement Learning Packt Packt
Generative Adversarial Networks Packt Packt
Other Books You May Enjoy Packt Packt

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