Python for TensorFlow Pocket Primer
Book Details
Format
Paperback / Softback
Book Series
Pocket Primer
ISBN-10
1683923618
ISBN-13
9781683923619
Publisher
Mercury Learning & Information
Imprint
Mercury Learning & Information
Country of Manufacture
US
Country of Publication
GB
Publication Date
Jun 17th, 2019
Print length
218 Pages
Weight
336 grams
Product Classification:
Programming & scripting languages: generalProgramming and scripting languages: general
Ksh 5,500.00
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As part of the best-selling Pocket Primer series, this book is designed to prepare programmers for machine learning and deep learning/TensorFlow topics. It begins with a quick introduction to Python, followed by chapters that discuss NumPy, Pandas, Matplotlib, and scikit-learn. The final two chapters contain an assortment of TensorFlow 1.x code samples, including detailed code samples for TensorFlow Dataset (which is used heavily in TensorFlow 2 as well). A TensorFlow Dataset refers to the classes in the tf.data.Dataset namespace that enables programmers to construct a pipeline of data by means of method chaining so-called lazy operators, e.g., map(), filter(), batch(), and so forth, based on data from one or more data sources.
Companion files with source code are available for downloading from the publisher by writing [email protected].
Features:
- A practical introduction to Python, NumPy, Pandas, Matplotlib, and introductory aspects of TensorFlow 1.x
- Contains relevant NumPy/Pandas code samples that are typical in machine learning topics, and also useful TensorFlow 1.x code samples for deep learning/TensorFlow topics
- Includes many examples of TensorFlow Dataset APIs with lazy operators, e.g., map(), filter(), batch(), take() and also method chaining such operators
- Assumes the reader has very limited experience
- Companion files with all of the source code examples (download from the publisher)
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