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This book is designed to prepare programmers for machine learning and deep learning TensorFlow topics. Author Oswald Campesato begins with a quick introduction to Python, followed by chapters that discuss NumPy, Pandas, Matplotlib, and scikit-learn. The book contains an assortment of TensorFlow 1.x code samples, including detailed code samples for TensorFlow Dataset, which is used heavily in TensorFlow 2 as well.
<ASIN:1683923618>
Author: Oswald Campesato
Publisher: Mercury Learning & Information
Date: June 2019
Pages: 200
ISBN: 978-1683923619
Print: 1683923618
Kindle: B07RS49B11
Audience: Python developers interested in TensorFlow
Level: Intermediate
Category: Artificial Intelligence
- 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)
For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.
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Administering Relational Databases on Microsoft Azure
Author: Prashanth Jayaram et al
Publisher: Independent
Pages: 622
ISBN: 979-8706128029
Print: B08Y4LBTP4
Kindle: B08XZQJHMK
Audience: Azure DBAs
Rating: 2 or 4 (see review for details)
Reviewer: Ian Stirk
This book aims to help you pass the Azure Relational Database exam DP-300, how does it fare?
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The Rust Programming Language, 2nd Ed
Author: Steve Klabnik and Carol Nichols
Publisher: No Starch Press
Date: June 2023
Pages: 560
ISBN: 978-1718503106
Print: 1718503105
Kindle: B0B7QTX8LL
Audience: Systems programmers
Rating: 4.8
Reviewer: Mike James
There's a new edition of what has become the standard text on Rust. Has it matured along with [ ... ]
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