Overview

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For detailed personal notes on Data Science, go visit my Github repo at https://github.com/monchewharry/datascience-m1-wsl2

The topics that covered in the github repo notes:

• Machine Learning workflow
• data preprocessing->Pipline
• data split
  • three-fold split
  • k-fold cross-validation
• algorithms
  • L1, L2 norm
  • (non)parametric models
  • supervised learning
  • unsupervised learning
  • reinforcement learning
• ensembles: bagging, boosting, stacking
• calibration
• model evaluation
• unbalanced data
• feature selection
• hyperparameter selection
• dimension reduction
• some terminology
• blackbox interpretation
• sklearn
• xgboost
• tensorflow