The Art of Machine Learning: A Hands-On Guide to Machine Learning with R
Matloff, Norman
Sold by HPB-Red, Dallas, TX, U.S.A.
AbeBooks Seller since 11 March 2019
Used - Soft cover
Condition: Used - Good
Quantity: 1 available
Add to basketSold by HPB-Red, Dallas, TX, U.S.A.
AbeBooks Seller since 11 March 2019
Condition: Used - Good
Quantity: 1 available
Add to basketConnecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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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:
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
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