Tensorflow Pocket Primer - by Oswald Campesato (Paperback)

About the Book

As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to TensorFlow 1.x fundamentals for basic machine learning algorithms in TensorFlow. It is intended to be a fast-paced introduction to various core features of TensorFlow, with code samples that cover deep learning and TensorFlow basics. The material in

Book Synopsis

No detailed description available for "TensorFlow Pocket Primer".

Review Quotes

"TensorFlow Pocket Primer introduces readers to TensorFlow 1x basics for machine learning algorithms, and is designed to be an introduction used either to supplement a course or for self-learning. It uses Python to cover code examples, assumes limited experience and background in the subject, and comes with supporting reference files containing all source code examples as a download from the publisher. From Cloud-based platforms to useful components of TensorFlow and their real-world applications, this primer will get anyone up and running in the shortest amount of time possible."

About the Author

Campesato Oswald:

Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).