Tutorials

There are two datasets for analyses:

There are 6 .ipynb notebooks:

Linear_Regression.ipynb: Implements Linear regression on Advertising data and generates ANOVA table for the same with the help of OLS(Ordinary Least Square) method.
Multiple_Linear_Regression.ipynb: Implements Multiple Linear regression on Advertising data with the help of scikit-learn.
PCA_Sklearn.ipynb: Implements Principal Component Analysis with scikit-learn.
Pandas_Tutorial.ipynb: Contains some basic exercises on the use of pandas.
Pandas_Tutorial2.ipynb: Contains some more exercises on the use of pandas.
Principal_Component_Analysis.ipynb: Implements Principal Component Analysis from scratch.
Testing_tutorial.ipynb: Implements some hypothesis testing exercises like Chisquare, t-test, ANOVA(One way and two way).

In some files, there are some additional exercises as well like visualization etc.

Name		Name	Last commit message	Last commit date
Latest commit History 30 Commits
Advertising.csv		Advertising.csv
Credit.csv		Credit.csv
Linear_Regression.ipynb		Linear_Regression.ipynb
Multiple_Linear_Regression.ipynb		Multiple_Linear_Regression.ipynb
PCA_Sklearn.ipynb		PCA_Sklearn.ipynb
Pandas_Tutorial.ipynb		Pandas_Tutorial.ipynb
Pandas_Tutorial_2.ipynb		Pandas_Tutorial_2.ipynb
Principal_Component_Analysis.ipynb		Principal_Component_Analysis.ipynb
README.md		README.md
Testing_tutorial.ipynb		Testing_tutorial.ipynb

Provide feedback