Mastering TensorFlow

Mastering TensorFlow: Design, Train, and Deploy High-Performance AI Systems
A Practical Guide to Deep Learning, TensorFlow Lite, and Production-Ready Machine Learning Pipelines Across Cloud, Mobile, and Edge Devices
Building powerful AI models is no longer the challenge, deploying them efficiently, scaling them reliably, and maintaining their performance across platforms is. As machine learning moves from experimentation to production, engineers face a new reality: models must not only work, but work everywhere, on servers, browsers, phones, and even microcontrollers.
Mastering TensorFlow is your complete guide to making that possible. Written for developers and ML practitioners who want practical results, this book shows you how to design, train, and deploy TensorFlow models that perform under real-world constraints. From efficient data pipelines to mobile deployment, you'll learn how to bridge the gap between a working prototype and a production-grade AI system.
You'll discover how to:

• Build and optimize deep learning models using TensorFlow 2.x and Keras APIs.
• Implement tf.data pipelines for scalable input processing and performance tuning.
• Use TensorFlow Lite, TensorFlow.js, and TensorFlow Micro to deploy models across devices and environments.
• Apply distributed training, mixed precision, and quantization for large-scale workloads.
• Integrate models into real applications using TensorFlow Serving, REST/gRPC APIs, and mobile frameworks.
• Monitor, version, and update models safely in production.