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TensorFlow Deep Learning Projects
TensorFlow Deep Learning Projects

TensorFlow Deep Learning Projects: 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning

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Profile Icon Rajalingappaa Shanmugamani Profile Icon Alexey Grigorev Profile Icon Srinivas Kulkarni
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€34.99
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2 (1 Ratings)
Paperback Mar 2018 320 pages 1st Edition
eBook
€25.19 €27.99
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€34.99
Subscription
Free Trial
Renews at €18.99p/m
Arrow left icon
Profile Icon Rajalingappaa Shanmugamani Profile Icon Alexey Grigorev Profile Icon Srinivas Kulkarni
Arrow right icon
€34.99
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2 (1 Ratings)
Paperback Mar 2018 320 pages 1st Edition
eBook
€25.19 €27.99
Paperback
€34.99
Subscription
Free Trial
Renews at €18.99p/m
eBook
€25.19 €27.99
Paperback
€34.99
Subscription
Free Trial
Renews at €18.99p/m

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TensorFlow Deep Learning Projects

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Key benefits

  • *Build efficient deep learning pipelines using the popular Tensorflow framework
  • *Train neural networks such as ConvNets, generative models, and LSTMs
  • *Includes projects related to Computer Vision, stock prediction, chatbots and more

Description

TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects. TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. You'll learn how to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing this, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation and use reinforcement learning techniques to play games. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.

Who is this book for?

This book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book.

What you will learn

  • •Set up the TensorFlow environment for deep learning
  • •Construct your own ConvNets for effective image processing
  • •Use LSTMs for image caption generation
  • •Forecast stock prediction accurately with an LSTM architecture
  • •Learn what semantic matching is by detecting duplicate Quora questions
  • •Set up an AWS instance with TensorFlow to train GANs
  • •Train and set up a chatbot to understand and interpret human input
  • •Build an AI capable of playing a video game by itself –and win it!
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 28, 2018
Length: 320 pages
Edition : 1st
Language : English
ISBN-13 : 9781788398060
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Product Details

Publication date : Mar 28, 2018
Length: 320 pages
Edition : 1st
Language : English
ISBN-13 : 9781788398060
Vendor :
Google
Category :
Languages :
Concepts :
Tools :

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Table of Contents

11 Chapters
Recognizing traffic signs using Convnets Chevron down icon Chevron up icon
Annotating Images with Object Detection API Chevron down icon Chevron up icon
Caption Generation for Images Chevron down icon Chevron up icon
Building GANs for Conditional Image Creation Chevron down icon Chevron up icon
Stock Price Prediction with LSTM Chevron down icon Chevron up icon
Create and Train Machine Translation Systems Chevron down icon Chevron up icon
Train and Set up a Chatbot, Able to Discuss Like a Human Chevron down icon Chevron up icon
Detecting Duplicate Quora Questions Chevron down icon Chevron up icon
Building a TensorFlow Recommender System Chevron down icon Chevron up icon
Video Games by Reinforcement Learning Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
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2 star 100%
1 star 0%
N31LD Apr 18, 2018
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
Three problems with this book.(1) The Kindle version does not render the code well. The code wraps and indentation does not hold up as the page width varies, so it's impossible to tell whether a line of code belongs to one level of indentation or another. Sure, I can download the code from the repo and look at it in Jupyter, but what's the use of the book about code if you can't read the code?(2) The text between the code chunks is frequently trivial, and in many cases should have just been comments in the code. e.g. "And finally, here's the code for training the model with minibatches:"(3) The book assumes a moderately high level of understanding of TensorFlow. Do not buy this book unless you already have a strong understanding of terms like "dropout", "flattenizer", "softmax", and "leaky ReLU activation". Terms like these are used continuously without explanation. If you don't already understand them, this book will not help you understand TensorFlow.Given (3), I have to wonder who the target audience is for this book - presumably if the reader already understands TensorFlow they will have access to code examples for different types of project. If the reader has data science skills but does not understand TensorFlow, it's not helpful. This book missed out on an important niche of helping data scientists learn TensorFlow through practical projects.
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