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Course Outline

Basics of Machine Learning

  1. Business Problems to Data Problems
  2. Broad Categories of Business Problems
  3. Supervised and Unsupervised Machine Learning Algorithm
  4. Drivers of ML algorithms
  5. Cost Functions
  6. A brief introduction to Gradient Descent
  7. Importance of Model Validation
  8. Methods of Model Validation
  9. Introduction to Cross-Validation and Average Error

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