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Resources - DSML

Python

Kaggle

  • The Kaggle Grandmasters Playbook: 7 Battle-Tested Modeling Techniques for Tabular Data (link)
  • Top solutions of the regression playground competitions in last one year (link)

Kaggle Competions

  • Predicting Optimal Fertilizers (link)
  • Predict Calorie Expenditure (link)
  • Binary Prediction with a Rainfall Dataset (link)
  • Regression with an Insurance Dataset (link)
  • Exploring Mental Health Data (link)
  • Loan Approval Prediction (link)
  • Regression of Used Car Prices (link)
  • Feature Engineering for House Prices (link)
  • House Prices - Advanced Regression Techniques (link)

Machine Learning

  • Visual Intro Decision Tree (link)
  • Bias and Variance (link)
  • explained.ai (link)
  • How to visualize decision trees (link)
  • dtreeviz : Decision Tree Visualization (link)
  • Beware Default Random Forest Importances (link)
  • Feature importances for scikit-learn machine learning models (link)
  • How to explain gradient boosting (link)
  • Gradient Boosted Regression Trees (link)
  • The Mechanics of Machine Learning (link)
  • Decision Tree: an algorithm that works like the human brain (link)
  • treeinterpreter (link)
  • Interpreting random forests (link)
  • Random forest interpretation with scikit-learn (link)
  • treeinterpreter - Interpreting Tree-Based Model’s Prediction of Individual Sample (link)
  • Demystify the random forest (link)
  • AutoML (link)

Visualization