diff --git a/books.md b/books.md index 573dc7b..7a8faf2 100644 --- a/books.md +++ b/books.md @@ -60,6 +60,7 @@ The following is a list of free and/or open source books on machine learning, st - [Automated Machine Learning in Action](https://www.manning.com/books/automated-machine-learning-in-action) - Qingquan Song, Haifeng Jin, and Xia Hu - Optimize every stage of your machine learning pipelines with powerful automation components and cutting-edge tools like AutoKeras and Keras Tuner. - [Distributed Machine Learning Patterns](https://www.manning.com/books/distributed-machine-learning-patterns) - Yuan Tang - Practical patterns for scaling machine learning from your laptop to a distributed cluster. - [Human-in-the-Loop Machine Learning: Active learning and annotation for human-centered AI](https://www.manning.com/books/human-in-the-loop-machine-learning) - Robert (Munro) Monarch - a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process. +- [Feature Engineering Bookcamp](https://www.manning.com/books/feature-engineering-bookcamp) - Maurucio Aniche - This book’s practical case-studies reveal feature engineering techniques that upgrade your data wrangling—and your ML results. ## Deep Learning