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Mastering TensorFlow: Design, Train, and Deploy High-Performance AI Systems: A Practical Guide to Deep Learning, TensorFlow Lite, and Production-Ready
Paperback
Publisher: Independently Published
Published: Nov 8 2025
Pages: 268
Weight: 1.04
Height: 0.56 Width: 7.00 Depth: 10.00
Language: English
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.
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.
Whether you're a data scientist expanding into engineering, a developer shipping AI features, or an ML engineer improving system performance, this book gives you the clarity, structure, and techniques to scale TensorFlow from concept to deployment.
If you're ready to move from it works on my machine to it performs everywhere, this is your next essential reference.
Build smarter systems. Train faster. Deploy confidently. Start mastering TensorFlow today.
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