A compact guide to mastering Tensor Flow 2, covering essential APIs, datasets, and practical applications for efficient machine learning and deep learning projects.Key Features Comprehensive guide to Tensor Flow 2Practical examples and code samples Companion files with source code and figures Book Description As part of the best-selling *Pocket Primer* series, this book introduces beginners to basic machine learning algorithms using Tensor Flow 2. It provides a fast-paced introduction to Tensor Flow, covering core features and machine learning basics with Python code samples. An appendix includes Keras-based code samples and explores MLPs, CNNs, RNNs, and LSTMs. The chapters illustrate how to solve various tasks, encouraging further reading to deepen your knowledge. The journey begins with an introduction to Tensor Flow 2, followed by essential APIs and datasets. You’ll explore linear regression and classifiers, learning to apply Tensor Flow to practical problems. The comprehensive appendix covers advanced topics like NLPs and deep learning architectures, enhancing your understanding of machine learning. Understanding these concepts is crucial for modern AI applications. This book transitions readers from basic Tensor Flow use to advanced machine learning techniques, blending theory with practical examples. Companion files with source code and figures enhance learning, making this an essential resource for mastering Tensor Flow and machine learning.What you will learn Master Tensor Flow 2 APIs Implement linear regression Work with classifiers Use Tensor Flow 2 datasets Understand eager execution Convert TF 1.x code to TF 2Who this book is for Developers with a basic understanding of Python and machine learning concepts will find this book ideal. It assumes familiarity with basic programming and data handling. Prior knowledge of Tensor Flow 1.x is beneficial but not required.]]>
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