This book will introduce you to the fundamentals of machine learning through TensorFlow. TensorFlow is Google’s new software library for deep learning that makes it straightforward for engineers to design and deploy sophisticated deep learning architectures. You will learn how to use TensorFlow to build systems capable of detecting objects in images, understanding human text, and predicting the properties of potential medicines. Furthermore, you will gain an intuitive understanding of TensorFlow’s potential as a system for performing tensor calculus and will learn how to use TensorFlow for tasks outside the traditional purview of machine learning.
Importantly, TensorFlow for Deep Learning is one of the first deep learning books written for practitioners. It teaches fundamental concepts through practical examples and builds understanding of machine learning foundations from the ground up. The target audience for this book is practicing developers, who are comfortable with designing software systems, but not necessarily with creating learning systems. At times we use some basic linear algebra and calculus, but we will review all necessary fundamentals. We also anticipate that our book will prove useful for scientists and other professionals who are comfortable with scripting, but not necessarily with designing learning algorithms.
Indicates new terms, URLs, email addresses, filenames, and file extensions.
Used for program listings, as well as within paragraphs to refer to program elements such as variable or function names, databases, data types, environment variables, statements, and keywords.
Constant width bold
Shows commands or other text that should be typed literally by the user.
Constant width italic
Shows text that should be replaced with user-supplied values or by values determined by context.
This element signifies a tip or suggestion.
This element signifies a general note.
This element indicates a warning or caution.
Supplemental material (code examples, exercises, etc.) is available for download at https://github.com/matroid/dlwithtf.
This book is here to help you get your job done. In general, if example code is offered with this book, you may use it in your programs and documentation. You do not need to contact us for permission unless you’re reproducing a significant portion of the code. For example, writing a program that uses several chunks of code from this book does not require permission. Selling or distributing a CD-ROM of examples from O’Reilly books does require permission. Answering a question by citing this book and quoting example code does not require permission. Incorporating a significant amount of example code from this book into your product’s documentation does require permission.
We appreciate, but do not require, attribution. An attribution usually includes the title, author, publisher, and ISBN. For example: “TensorFlow for Deep Learning by Bharath Ramsundar and Reza Bosagh Zadeh (O’Reilly). Copyright 2018 Reza Zadeh, Bharath Ramsundar, 978-1-491-98045-3.”
If you feel your use of code examples falls outside fair use or the permission given above, feel free to contact us at firstname.lastname@example.org.
Safari (formerly Safari Books Online) is a membership-based training and reference platform for enterprise, government, educators, and individuals.
Members have access to thousands of books, training videos, Learning Paths, interactive tutorials, and curated playlists from over 250 publishers, including O’Reilly Media, Harvard Business Review, Prentice Hall Professional, Addison-Wesley Professional, Microsoft Press, Sams, Que, Peachpit Press, Adobe, Focal Press, Cisco Press, John Wiley & Sons, Syngress, Morgan Kaufmann, IBM Redbooks, Packt, Adobe Press, FT Press, Apress, Manning, New Riders, McGraw-Hill, Jones & Bartlett, and Course Technology, among others.
For more information, please visit http://oreilly.com/safari.
We have a web page for this book, where we list errata, examples, and any additional information. You can access this page at http://bit.ly/tensorflowForDeepLearning.
To comment or ask technical questions about this book, send email to email@example.com.
For more information about our books, courses, conferences, and news, see our website at http://www.oreilly.com.
Find us on Facebook: http://facebook.com/oreilly
Follow us on Twitter: http://twitter.com/oreillymedia
Watch us on YouTube: http://www.youtube.com/oreillymedia
Reza is thankful to the open source communities on which much of software and computer science is based. Open source software is one of the largest concentrations of human knowledge ever created, and this book would have been impossible without the entire community behind it.