|
Topic |
Resources |
1 |
Introduction |
Introduction.pdf |
2 |
Setup python (Anaconda or Colab) |
Setup |
3 |
How to format data for scikit-learn |
Format_Data_For_Machine_Learning.ipynb |
4 |
Linear regression using scikit-learn |
LinearRegression.ipynb |
5 |
Train test split |
TrainTestSplit.ipynb, BostonSplit.ipynb |
6 |
Decision trees for classification |
DecisionTreesClassification.ipynb |
7 |
Decision trees for regression |
DecisionTreesRegression.ipynb |
8 |
Visualize decision trees using Python |
DecisionTreesVisualization.ipynb |
9 |
Bagged trees using Python |
BaggedTrees.ipynb |
10 |
Random Forests using Python |
RandomForests.ipynb |
11 |
Conclusion |
Conclusion.pdf |