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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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Software Mistakes and Tradeoffs (Manning)
Author: Tomasz Lelek and Jon Skeet
Publisher: Manning
Date: June 2022
Pages: 426
ISBN: 978-1617299209
Print: 1617299200
Audience: C# developers
Rating: 4
Reviewer: Mike James
We all make mistakes - do you want to read about them?
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C++ Programming, 6th Ed (In Easy Steps)
Author: Mike McGrath
Publisher: In Easy Steps
Date: April 2022
Pages: 192
ISBN: 978-1840789713
Print: 1840789719
Kindle: B09V2T9SJD
Audience: Developers wanting to learn C++
Reviewer: Mike James
This is the 6th edition of a slim book on C++. Can you really learn C++ in easy steps?
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