Practical Machine Learning Tools and Techniques
Machine learning provides an exciting set of technologies that includes practical tools for analyzing data and making predictions but also powers the latest advances in artificial intelligence. We have written a book that provides a highly accessible introduction to the area but also caters for readers who want to delve into the more mathematical techniques available in modern probabilistic modeling and deep learning approaches. Chris Pal has joined Ian Witten, Eibe Frank, and Mark Hall for the fourth edition, and his expertise in probabilistic models and deep learning has greatly extended the book’s coverage.
Machine Learning for Data Streams
The “Machine Learning for Data Streams with Practical Examples in MOA” textbook is a resource intended to help students and practitioners enter the field of machine learning and data mining for data streams. The online version of the book is now complete and will remain available online for free.
- Series: Adaptive Computation and Machine Learning series
- Hardcover: 288 pages
- Publisher: The MIT Press (March 2, 2018)
- Language: English