Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples.
The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build models using customer estimators. Further, it explains how to use TensorFlow 2.0 API to build machine learning and deep learning models for image classification using the standard as well as custom parameters.
You'll review sequence predictions, saving, serving, deploying, and standardized datasets, and then deploy these models to production. All the code presented in the book will be available in the form of executable scripts at Github which allows you to try out the examples and extend them in interesting ways.
What You'll Learn
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Pramod Singh is currently playing a role of Machine Learning Expert at Walmart Labs. He has extensive hands-on experience in machine learning, deep learning, AI, data engineering, designing algorithms and application development. He has spent more than 10 years working on multiple data projects at different organizations. He's the author of three books -Machine Learning with PySpark, Learn PySpark and Learn TensorFlow 2.0. He is also a regular speaker at major conferences such as O'Reilly's Strata and AI conferences. Pramod holds a BTech in electrical engineering from B.A.T.U, and an MBA from Symbiosis University. He has also done Data Science certification from IIM-Calcutta. He lives in Bangalore with his wife and three-year-old son. In his spare time, he enjoys playing guitar, coding, reading, and watching football.
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