Hapke, Hannes
Building Machine Learning Pipelines: Automating Model Life Cycles with Tensorflow
- ISBN 13:
- 9781492053194
- author:
- Hapke, Hannes
- format:
- Paperback / softback
- publisher:
- O'Reilly Media, Inc, USA
- language:
- English
- Publication Year:
- 2020
- Pages:
- 366
- Dimensions:
- 23.3 x 17.8 x 1.9 centimetres (0
- Genre:
- Computers, Graphics & Design, Computers,
- Condition:
- New
- Availability:
- Item usually sent within 10 working days
Description
Automating machine learning pipelines with TensorFlow is crucial for effective deployment and minimizing maintenance time. This practical guide provides step-by-step instructions on how to build, orchestrate, and deploy machine learning pipelines using the TensorFlow ecosystem.
You'll learn how to work with data using TensorFlow Data Validation and TensorFlow Transform, analyze models in detail with TensorFlow Model Analysis, examine fairness and bias in model performance, and deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices. By following these techniques and tools, you can cut deployment time from days to minutes and focus on developing new models.
Whether you're a data scientist, machine learning engineer, DevOps engineer, or manager, this book provides the knowledge and skills needed to successfully productize your data science projects and accelerate your organization's machine learning initiatives.
Related Products
Related Products
Tensorflow 2 Pocket - Reference: Building and - Deploying Machine Learning - Models
Tung, K. C.
Machine Learning Production Systems: Engineering Machine Learning Models and Pipelines
Crowe, Robert
Machine Learning Engineering - with Python: Manage the - production life cycle of - machine learning models - using MLOps with practical - examples
McMahon, Andrew P.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems
Geron, Aurelien
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition
Raschka, Sebastian