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Link to Content:
DataCamp Machine Learning Toolbox

Created/Published/Taught by:
DataCamp
Zachary Deane-Mayer
Max Kuhn
Nick Carchedi
Tom Jeon

Content Found Via:
DataCamp

Free? Partially: Some Free Content, Some Paid

Cost Range:
$0.00 - $29.00

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From DataCamp:

“Machine learning is the study and application of algorithms that learn from and make predictions on data. From search results to self-driving cars, it has manifested itself in all areas of our lives and is one of the most exciting and fast-growing fields of research in the world of data science. This course teaches the big ideas in machine learning: how to build and evaluate predictive models, how to tune them for optimal performance, how to preprocess data for better results, and much more. The popular caret R package, which provides a consistent interface to all of R’s most powerful machine learning facilities, is used throughout the course.”

This course consists of five chapters:

  1. Regression models: fitting them and evaluating their performance
  2. Classification models: fitting them and evaluating their performance
  3. Tuning model parameters to improve performance
  4. Preprocessing your data
  5. Selecting models: a case study in churn prediction

Recommended Prerequisites: none specified; familiarity with R

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