Machine Learning Model Serving Patterns and Best Practices

eBook Details:

• Paperback: 336 pages
• Publisher: WOW! eBook (December 30, 2022)
• Language: English
• ISBN-10: 1803249900
• ISBN-13: 978-1803249902

eBook Description:

Machine Learning Model Serving Patterns and Best Practices: Become a successful machine learning professional by effortlessly deploying machine learning models to production and implementing cloud-based machine learning models for widespread organizational use

Serving patterns enable data science and ML teams to bring their models to production. Most ML models are not deployed for consumers, so ML engineers need to know the critical steps for how to serve an ML model.

This book will cover the whole process, from the basic concepts like stateful and stateless serving to the advantages and challenges of each. Batch, real-time, and continuous model serving techniques will also be covered in detail. Later chapters will give detailed examples of keyed prediction techniques and ensemble patterns. Valuable associated technologies like TensorFlow severing, BentoML, and RayServe will also be discussed, making sure that you have a good understanding of the most important methods and techniques in model serving. Later, you’ll cover topics such as monitoring and performance optimization, as well as strategies for managing model drift and handling updates and versioning. The book will provide practical guidance and best practices for ensuring that your model serving pipeline is robust, scalable, and reliable. Additionally, this book will explore the use of cloud-based platforms and services for model serving using AWS SageMaker with the help of detailed examples.

• Explore specific patterns in model serving that are crucial for every data science professional
• Understand how to serve machine learning models using different techniques
• Discover the various approaches to stateless serving
• Implement advanced techniques for batch and streaming model serving
• Get to grips with the fundamental concepts in continued model evaluation
• Serve machine learning models using a fully managed AWS Sagemaker cloud solution

By the end of this Machine Learning Model Serving Patterns and Best Practices book, you’ll be able to save and serve your model using state-of-the-art techniques.