November 2020
Intermediate to advanced
314 pages
5h 55m
English
Overview
In 'Learn TensorFlow Enterprise,' you'll explore how to build, manage, and scale machine learning models utilizing Google's TensorFlow Enterprise. Through rich hands-on exercises, this book guides you through optimizing workflows for enterprise-grade AI applications. By the end, you'll gain familiarity in developing production-ready solutions that are robust and scalable.
What this Book will help me do
- Set up and optimize TensorFlow Enterprise environments on Google Cloud Platform for AI projects.
- Develop and train scalable machine learning models using GPUs and TPUs effectively.
- Implement best practices for data pipelines and model deployment in production environments.
- Leverage TensorFlow Enterprise tools for distributed training and hyperparameter tuning.
- Master techniques for optimizing models to improve performance and reliability in real-world applications.
Author(s)
None Tung is a seasoned machine learning engineer with extensive experience working with TensorFlow in both development and production environments. Leveraging her proficiency in Google's AI and cloud platforms, she brings insights into streamlining ML workflows for enterprise applications. Her writing reflects a commitment to helping learners achieve practical and deployable solutions.
Who is it for?
This book is ideal for data scientists, machine learning engineers, and cloud practitioners keen on developing production-grade AI models. If you are familiar with basic machine learning principles and eager to explore TensorFlow Enterprise's cloud capabilities, this guide is for you. You'll learn how to scale and manage workloads effectively, making it a perfect fit for professionals seeking to enhance their expertise in enterprise solutions.
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