November 2017
Intermediate to advanced
304 pages
6h 58m
English
Overview
Machine Learning with TensorFlow 1.x is your comprehensive guide to utilizing TensorFlow 1.x for solving modern machine learning problems. Throughout the book, you will explore practical projects, ranging from training classifiers to deploying neural networks for real-world applications. With clear instructions and industry insights, this book prepares you to apply TensorFlow 1.x effectively in your workflows.
What this Book will help me do
- Understand the key concepts of TensorFlow 1.x and its role in machine learning workflows.
- Build and train deep learning models using TensorFlow's advanced features and visualization tools.
- Apply machine learning techniques to practical scenarios such as text and image analysis.
- Deploy machine learning solutions at scale, utilizing multi-GPU setups and cloud services like AWS.
- Bridge the gap from theoretical understanding to real-world implementation, including model conversion and optimization.
Author(s)
None Hua, None Ahmed, and None Ul Azeem are experienced professionals in machine learning and software engineering. With backgrounds that combine academic research and industry application, they bring invaluable insights into the practical aspects of using TensorFlow. Their expertise spans multiple industries, ensuring readers have access to well-rounded and actionable guidance.
Who is it for?
Machine Learning with TensorFlow 1.x is designed for data scientists and developers looking to master TensorFlow for machine learning applications. This book is ideal for professionals migrating from other platforms or starting with TensorFlow and focuses on real-world use cases. While no domain-specific knowledge is required, readers should be familiar with Python programming and basic linear algebra.
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