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.
Author: Oswald Campesato
Publisher: Mercury Learning & Information
Date: June 2019
Audience: Python developers interested in TensorFlow
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.
For more Book Watch just click.
Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some, but by no means all, of the books in Book Watch are eventually reviewed.
To have new titles included in Book Watch contact BookWatch@i-programmer.info
Follow @bookwatchiprog on Twitter or subscribe to I Programmer's Books RSS feed for each day's new addition to Book Watch and for new reviews.