Designing Machine Learning Systems
Chip Huyen is a co-founder of Claypot AI, a real-time machine learning platform. She has assisted some of the world's largest corporations in developing and deploying machine learning systems through her work with NVIDIA, Netflix, and Snorkel AI. She teaches CS 329S: Machine Learning Systems Design at Stanford, and this book is based on her lecture notes.
Machine learning systems are both complicated and one-of-a-kind. Complex because they are made up of numerous components and involve numerous stakeholders. They are distinct because they are data dependant, with data altering greatly from one use case to the next. Designing Machine Learning Systems will teach you how to develop ML systems that are dependable, scalable, maintainable, and adaptable to changing environments and business requirements.
Claypot AI co-founder and author Chip Huyen evaluates each design decision, such as how to handle and create training data, which features to utilize, how often to retrain models, and what to monitor, in the context of how it might help your system as a whole achieve its goals. The iterative structure in this book is supported by several references.
Designing Machine Learning Systems will assist you in dealing with problems such as:
- Data engineering and selecting the appropriate metrics to address a business problem
- Automating the process of generating, analyzing, deploying, and updating models on a continuous basis.
- Creating a monitoring system to detect and address issues that your models may encounter in production.
- Creating an ML platform that can serve several use cases
- Creating accountable machine learning systems
Author: Chip Huyen
Link to buy: https://www.amazon.com/Designing-Machine-Learning-Systems-Production-Ready/dp/1098107969/
Ratings: 4.9 out of 5 stars (from 17 reviews)
Best Sellers Rank: #3,908 in Books
#1 in Machine Theory (Books)
#1 in Business Intelligence Tools
#1 in Artificial Intelligence (Books)
