首页Python Deep Learning, 2nd Edition
A strong foundation on neural networks and deep learning with Python libraries. Explore advanced deep learning techniques and their applications across computer vision and NLP. Learn how a computer can navigate in complex environments with reinforcement learning.
Python Deep Learning
Exploring deep learning techniques and neural network
architectures with PyTorch, Keras, and TensorFlow
BIRMINGHAM - MUMBAI
Python Deep Learning
Copyright © 2019 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 Editor: Pravin Dhandre
Acquisition Editor: Yogesh Deokar
Content Development Editor: Nathanya Dias
Technical Editor: Kushal Shingote
Copy Editor: Safis Editing
Project Coordinator: Kirti Pisat
Proofreader: Safis Editing
Indexer: Rekha Nair
Graphics: Jisha Chirayil
Production Coordinator: Priyanka Dhadke
First published: October 2016
Second edition: January 2019
Production reference: 1110119
Published by Packt Publishing Ltd.
35 Livery Street
B3 2PB, UK.
Mapt is an online digital library that gives you full access to over 5,000 books and videos, as
well as industry leading tools to help you plan your personal development and advance
your career. For more information, please visit our website.
Spend less time learning and more time coding with practical eBooks and Videos
from over 4,000 industry professionals
Improve your learning with Skill Plans built especially for you
Get a free eBook or video every month
Mapt is fully searchable
Copy and paste, print, and bookmark content
Did you know that Packt offers eBook versions of every book published, with PDF and
ePub files available? You can upgrade to the eBook version at www.packtpub.com and as a
print book customer, you are entitled to a discount on the eBook copy. Get in touch with us
at email@example.com for more details.
At www.packtpub.com, you can also read a collection of free technical articles, sign up for a
range of free newsletters, and receive exclusive discounts and offers on Packt books and
About the authors
Ivan Vasilev started working on the first open source Java Deep Learning library with GPU
support in 2013. The library was acquired by a German company, where he continued its
development. He has also worked as machine learning engineer and researcher in the area
of medical image classification and segmentation with deep neural networks. Since 2017 he
has focused on financial machine learning. He is working on a Python open source
algorithmic trading library, which provides the infrastructure to experiment with different
ML algorithms. The author holds an MSc degree in Artificial Intelligence from The
University of Sofia, St. Kliment Ohridski.
Daniel Slater started programming at age 11, developing mods for the id Software game
Quake. His obsession led him to become a developer working in the gaming industry on
the hit computer game series Championship Manager. He then moved into finance,
working on risk- and high-performance messaging systems. He now is a staff engineer
working on big data at Skimlinks to understand online user behavior. He spends his spare
time training AI to beat computer games. He talks at tech conferences about deep learning
and reinforcement learning; his blog can be found at www.danielslater.net. His work in
this field has been cited by Google.
Gianmario Spacagna is a senior data scientist at Pirelli, processing sensors and telemetry
data for internet of things (IoT) and connected-vehicle applications. He works closely with
tire mechanics, engineers, and business units to analyze and formulate hybrid, physics-
driven, and data-driven automotive models. His main expertise is in building ML systems
and end-to-end solutions for data products. He holds a master's degree in telematics from
the Polytechnic of Turin, as well as one in software engineering of distributed systems from
KTH, Stockholm. Prior to Pirelli, he worked in retail and business banking (Barclays), cyber
security (Cisco), predictive marketing (AgilOne), and did some occasional freelancing.
- 我的内容管理 收起
- 我的资源 快来上传第一个资源
- 我的收益 登录查看自己的收益
- 我的积分 登录查看自己的积分
- 我的C币 登录后查看C币余额