Keras 3 Deep Learning: Build High-Performance, Production-Ready Neural Networks Across TensorFlow, PyTorch, and JAX

Name: Keras 3 Deep Learning: Build High-Performance, Production-Ready Neural Networks Across TensorFlow, PyTorch, and JAX
Brand: Independently Published
SKU: 9798279357710
Price: 2716.0 INR
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by Frank Reiniger

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ISBN13: 9798279357710
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: December 21, 2025
Pages: 200
Original Price: USD 25.99
Language: English
Edition: N/A
Item Weight: 354 grams
BISAC Subject(s): Data Science / Neural Networks

About The Book

Keras 3 Deep Learning:
Build High-Performance, Production-Ready Neural Networks Across TensorFlow, PyTorch, and JAX

What if you could write a deep learning model once, and run it anywhere, at scale, with confidence?

Keras 3 Deep Learning is written for practitioners who are done choosing sides. TensorFlow, PyTorch, or JAX should be execution details, not architectural constraints. This book shows you how to build high-performance, production-ready neural networks using Keras 3's multi-backend design, so your models stay portable, scalable, and maintainable from first experiment to real deployment.

At its core, this book solves a problem modern ML teams face every day: fragmented workflows. Research code lives in one framework, production lives in another, and scaling introduces yet another layer of complexity. Keras 3 changes that. This book teaches you how to take advantage of that shift, without sacrificing performance, control, or engineering rigor.

You will learn how to design models that run consistently across TensorFlow, PyTorch, and JAX, how to choose backends deliberately based on hardware and workload, and how to build data pipelines that keep accelerators busy instead of idle. You will move beyond toy examples into distributed training, mixed precision, profiling, debugging, and automated hyperparameter search, using workflows that reflect how production systems actually operate.

Along the way, you will gain the ability to:

Build portable models with the Sequential and Functional APIs that scale cleanly across backends
Construct real data pipelines using Pandas, NumPy, tf.data, and PyTorch DataLoader without duplication
Optimize training with modern optimizers, learning-rate schedules, and regularization techniques
Scale beyond a single machine using distributed strategies, cluster orchestration, and tuning workflows
Integrate with TensorBoard, Keras Recommenders, and custom backend extensions for real-world systems

This is not a theory book. It is a practical, engineering-focused guide for AI engineers, ML practitioners, and data scientists who need results that survive production constraints.

If you are ready to stop rewriting models, stop guessing about performance, and start building deep learning systems that work across frameworks and infrastructure, get your copy of Keras 3 Deep Learning today.

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