Price: $49.99 - $30.07
(as of Sep 15, 2024 10:09:33 UTC – Details)
Learn to expertly apply a range of machine learning methods to real data with this practical guide.
Packed with real datasets and practical examples, The Art of Machine Learning will help you develop an intuitive understanding of how and why ML methods work, without the need for advanced math.
As you work through the book, you’ll learn how to implement a range of powerful ML techniques, starting with the k-Nearest Neighbors (k-NN) method and random forests, and moving on to gradient boosting, support vector machines (SVMs), neural networks, and more.
With the aid of real datasets, you’ll delve into regression models through the use of a bike-sharing dataset, explore decision trees by leveraging New York City taxi data, and dissect parametric methods with baseball player stats. You’ll also find expert tips for avoiding common problems, like handling “dirty” or unbalanced data, and how to troubleshoot pitfalls.
You’ll also explore:
How to deal with large datasets and techniques for dimension reductionDetails on how the Bias-Variance Trade-off plays out in specific ML methodsModels based on linear relationships, including ridge and LASSO regressionReal-world image and text classification and how to handle time series data
Machine learning is an art that requires careful tuning and tweaking. With The Art of Machine Learning as your guide, you’ll master the underlying principles of ML that will empower you to effectively use these models, rather than simply provide a few stock actions with limited practical use.
Requirements: A basic understanding of graphs and charts and familiarity with the R programming language
From the Publisher
About the Author
Norman Matloff is an award-winning teacher at UC Davis, with a PhD in Mathematics from UCLA. He is the author of a number of books in the data science area, and his software and web tutorials are used all over the world. His book, Statistical Regression and Classification: from Linear Models to Machine Learning, was the recipient of the 2017 Ziegel Award, given by the prominent technical journal Technometrics. Matloff is frequently asked to give keynote addresses at data science conferences and he also writes about social issues. He was the recipient of the Distinguished Public Service Award from UC Davis and is also the author of The Art of Debugging with GDB, DDD, and Eclipse and The Art of R Programming (both No Starch Press).
About the Publisher
No Starch Press has published the finest in geek entertainment since 1994, creating both timely and timeless titles like Python Crash Course, Python for Kids, How Linux Works, and Hacking: The Art of Exploitation. An independent, San Francisco-based publishing company, No Starch Press focuses on a curated list of well-crafted books that make a difference. They publish on many topics, including computer programming, cybersecurity, operating systems, and LEGO. The titles have personality, the authors are passionate experts, and all the content goes through extensive editorial and technical reviews. Long known for its fun, fearless approach to technology, No Starch Press has earned wide support from STEM enthusiasts worldwide.
Publisher : No Starch Press (January 9, 2024)
Language : English
Paperback : 272 pages
ISBN-10 : 1718502109
ISBN-13 : 978-1718502109
Item Weight : 2.31 pounds
Dimensions : 7 x 0.64 x 9.25 inches
