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Thakur Abhishek - TensorFlow Deep Learning Projects

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Thakur Abhishek TensorFlow Deep Learning Projects

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Key Features Projects on implementing high performance deep learning models with Tensorflow Master the techniques to train different kinds of neural networks with real-world use-cases such as image processing, natural language processing, and more Your one-stop guide to master deep learning with Tensorflow in the best possible manner Book DescriptionTensorflow is one of the most popular frameworks out there, used for machine learning and more recently, deep learning. It provides a fast, 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 12 real-world projects.Starting with setting up the right Tensorflow environment for deep learning, you will see how you can train different types of deep learning models using Tensorflow - including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and more. While doing so, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, enterprise AI, natural language processing, to name a few. You will train high performance models to generate captions for images automatically, predict stocks performance, create intelligent chatbots, perform large-scale text classification and more. Some advanced aspects like implementation on an enterprise-scale and reinforcement learning are also covered in this book.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 to tackle any kind of problem.What you will learn Set up the Tensorflow environment for deep learning Construct your own convnets for effective image processing Use LSTMs for caption generation for images Forecast stock prediction accurately with a LSTM architecture Learn what semantic matching is by detecting duplicate Quora questions Set up an AWS instance for distributed computing with Tensorflow to classify large amounts of Images Train and set up an intelligent chatbot to understand and interpret human input Build an AI capable of playing Pacman by itself and winning

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TensorFlow Deep Learning Projects 10 real-world projects on computer - photo 1
TensorFlow Deep Learning Projects
10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning
Luca Massaron
Alberto Boschetti
Alexey Grigorev
Abhishek Thakur
Rajalingappaa Shanmugamani

BIRMINGHAM - MUMBAI TensorFlow Deep Learning Projects Copyright 2018 Packt - photo 2

BIRMINGHAM - MUMBAI
TensorFlow Deep Learning Projects

Copyright 2018 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Commissioning Editors: Amey Varangaonkar
Acquisition Editor: Viraj Madhav
Content Development Editors: Snehal Kolte
Technical Editor: Dharmendra Yadav
Copy Editor: Safis Editing
Project Coordinator: Manthan Patel
Proofreader: Safis Editing
Indexers: Rekha Nair
Graphics: Tania Dutta
Production Coordinator: Shraddha Falebhai

First published: March 2018

Production reference: 1270318

Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.

ISBN 978-1-78839-806-0

www.packtpub.com

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Contributors
About the authors

Luca Massaron is a data scientist and marketing research director specialized in multivariate statistical analysis, machine learning, and customer insight, with 10+ years experience of solving real-world problems and generating value for stakeholders using reasoning, statistics, data mining, and algorithms. Passionate about everything on data analysis and demonstrating the potentiality of data-driven knowledge discovery to both experts and non-experts, he believes that a lot can be achieved by understanding in simple terms and practicing the essentials of any discipline.

I would like to thank Yukiko and Amelia for their continued support, help, and loving patience.


Alberto Boschetti is a data scientist with strong expertise in signal processing and statistics. He holds a PhD in telecommunication engineering and lives and works in London. In his work, he faces daily challenges spanning natural language processing, machine learning, and distributed processing. He is very passionate about his job and always tries to stay up to date on the latest development in data science technologies, attending meetups, conferences, and other events.

AlexeyGrigorev is a skilled data scientist, machine learning engineer, and software developer with more than 8 years of professional experience. He started his career as a Java developer working at a number of large and small companies, but after a while he switched to data science. Right now, Alexey works as a data scientist at Simplaex, where, in his day-to-day job, he actively uses Java and Python for data cleaning, data analysis, and modeling. His areas of expertise are machine learning and text mining.

I would like to thank my wife, Larisa, and my son, Arkadij, for their patience and support while I was working on the book.

Abhishek Thakur is a data scientist. His focus is mainly on applied machine learning and deep learning, rather than theoretical aspects. He completed his master's in computer science at the University of Bonn in early 2014. Since then, he has worked in various industries, with a research focus on automatic machine learning. He likes taking part in machine learning competitions and has attained a third place in the worldwide rankings on the popular website Kaggle.

Rajalingappaa Shanmugamani is currently a deep learning lead at SAP, Singapore. Previously, he worked and consulted at various startups, developing computer vision products. He has a master's from IIT Madras, his thesis having been based on the applications of computer vision in manufacturing. He has published articles in peer-reviewed journals, and spoken at conferences, and applied for a few patents in machine learning. In his spare time, he coaches programming and machine learning to school students and engineers.

I thank my spouse Ezhil, family and friends for their immense support. I thank all the teachers, colleagues, managers and mentors from whom I have learned a lot.
About the reviewer

Marvin Bertin is an online course author and technical book editor focused on deep learning, computer vision, and NLP with TensorFlow. He holds a bachelor's in mechanical engineering and a master's in data science. He has worked as an ML engineer and data scientist in the Bay Area, focusing on recommender systems, NLP, and biotech applications. He currently works at a start-up that develops deep learning (AI) algorithms for early cancer detection.

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