Lecture

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Lecture notes

  1. Introduction
  2. Machine Learning
  3. Python
  4. Business Understanding
  5. Data Understanding
  6. Data Preparation
  7. Modeling
  8. Evaluation
  9. Ensemble Models
  10. Deployment
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