Machine Learning with R
Expert techniques for predictive modeling, 3rd Edition
by Brett Lantz
Should I read this?
Recommended by 1 source and appears in Machine Learning, Programming, and Data Science.
Solve realworld data problems with R and machine learning. Key Features Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.5 and beyond Harness the power of R to build flexible, effective, and transparent machine learning models Learn quickly with a clear, handson guide by experienced machine ...
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Why recommended
Recommended by 1 source and appears in Machine Learning, Programming, and Data Science.
Recommended by notable people
People and public figures who have recommended this book.
Recommendation Signals
Recommendation proof is sourced from public posts, interviews, reading lists, and cited references.
Kirk Borne
“[FREE eBook] Learn Classification & Regression in a Weekend: ———— #BigData #MachineLearning #Algorithms #DataScience #Statistics #DataMining #AI #PredictiveAnalytics #Rstats #DataScientists #abdsc —— Then go deeper with this book:”
Appears In
Not sure if this is the right fit?
Consider Life 3.0 by Max Tegmark. Recommended by 18 sources.
“Life 3.0 reads like a long, wide-ranging conversation with a physicist who loves big if-then thought experiments. The useful part is its panoramic sweep across possible AI futures—from job automation to cosmic colonization—forcing you to consider timelines you might otherwise avoid. The limitation is that the speculative breadth often outruns the depth; chapters can feel meandering, and some readers will find the cosmic-scale scenarios too detached from practical concerns, making it hard to ground in real urgency.”
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Each recommendation is collected from a public source — interviews, articles, or curated lists — and linked to its original URL. Books with many verifiable recommendations from respected people rank higher.