Introduction to Scikit-Learn

This talk (video here) was for a Data Science Go (DSGO) Virtual Workshop on October 25, 2020.

Agenda

	Topic	Resources
1	Introduction	Introduction.pdf
2	Setup python (Anaconda or Colab)	Setup
3	How to format data for scikit-learn>Setup	FormatDataForMachineLearning.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	Logistic Regression using Python	LogisticRegression.ipynb, LogisticOneVsAll.ipynb
12	Conclusion	Conclusion.pdf
13	Bonus Content (not in presentation)	How to Speed Up Scikit-Learn Model Training