Tung Learn TensorFlow Enterprise

Build, manage, and scale machine learning workloads seamlessly using Google's TensorFlow Enterprise
1. Auflage 2020
ISBN: 978-1-80020-487-4
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 314 Seiten

No detailed description available for "Learn TensorFlow Enterprise".

Autoren/Hrsg.

Tung, KC

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware

Inhaltsverzeichnis

Table of Contents - Overview of TensorFlow Enterprise
- Running TensorFlow Enterprise in Google AI Platform
- Data Preparation and Manipulation Techniques
- Reusable Models and Scalable Data Pipelines
- Training at Scale

- Hyperparameter Tuning
- Model Optimization

- Best Practices for Model Training and Performance
- Serving a TensorFlow Model

Über Autor(innen)

Tung KC:

KC Tung is a cloud solution architect at Microsoft and specializes in machine learning, as well as AI model development and deployment. He has a Ph.D. in biophysics from the University of Texas Southwestern Medical Center in Dallas and has spoken at the 2018 O'Reilly AI Conference in San Francisco and the 2019 O'Reilly TensorFlow World Conference in San Jose. He has worked on building data ingestion and feature engineering pipelines for custom datasets in cloud environments. He has also delivered machine learning models for scalable deployment. He is a Microsoft certified AI engineer and data engineer.