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Ml Notes 02

End-to-End Machine Learning

  1. Understand big picture
  2. Get the data
  3. Discover and visualize the data to gain insights.
  4. Prepare the data for Machine Learning algorithms.
  5. Select a model and train it.
  6. Fine-tune your model.
  7. Present your solution.

  8. Launch, monitor, and maintain your system.

  9. Understand big picture
    • frame the problem
    • check assumptions
  10. Get the data
    • understand data, distributions
    • scales, units
    • train, test split
  11. Discover and visualize the data to gain insights.
    • visualization
    • correlations
  12. Prepare the data for Machine Learning algorithms.
    • data cleaning
      • get rid of rows
      • get rid of columns
      • fill with a value
    • text / categorical values transform
    • feature scaling
    • pipelines
  13. Select a model and train it.
    • training and evaluating on the training set
    • cross validation
    • save model
  14. Fine-tune your model.
    • Grid Search
    • Randomized Search
  15. Present your solution.
  16. Launch, monitor, and maintain your system.