×
Mixed media product
September 2019
9781683924609
More details
- Publisher
Mercury Learning & Information - Published
18th September 2019 - ISBN 9781683924609
- Language English
- Pages 252 pp.
- Size 6" x 9"
$35.95
E-Book (ePub)
August 2019
9781683924593
More details
- Publisher
Mercury Learning & Information - Published
27th August 2019 - ISBN 9781683924593
- Language English
- Pages 252 pp.
- Size 6" x 9"
$27.95
Lib E-Book
Library E-Books
We have signed up with three aggregators who resell networkable e-book editions of our titles to academic libraries. These aggregators offer a variety of plans to libraries, such as simultaneous access by multiple library patrons, and access to portions of titles at a fraction of list price under what is commonly referred to as a “patron-driven demand” model.
These editions, priced at par with simultaneous hardcover editions of our titles, are not available direct from Stylus, but only from the following aggregators:
- Ebook Library, a service of Ebooks Corporation Ltd. of Australia
- ebrary, based in Palo Alto, a subsidiary of ProQuest
- EBSCO / netLibrary, Alabama
as well as through the following wholesalers: The Yankee Book Peddler subsidiary of Baker & Taylor, Inc.
August 2019
9781683924616
More details
- Publisher
Mercury Learning & Information - Published
27th August 2019 - ISBN 9781683924616
- Language English
- Pages 252 pp.
- Size 6" x 9"
$99.95
As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various “core” features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by emailing proof of purchase to info@merclearning.com.
Features:
- Uses Python for code samples
- Covers TensorFlow 2 APIs and Datasets
- Includes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMs
- Features the companion files with all of the source code examples and figures (download from the publisher)
1: Introduction to TensorFlow 2
2: Useful TensorFlow 2 APIs
3: TensorFlow 2 Datasets
4: Linear Regression
5: Working with Classifiers
Appendix: TF2, Keras, and Advanced Topics
Index
On the Companion Files:
(available from the publisher for downloading)
- Source code samples from the text
- Figures
Oswald Campesato
Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).