Intro to ML

This project was done under Programming Club, Science and Technology Council. The project was aimed at introducing the basics of Machine Learning.

Outcomes:

• Got introduced to the basic libraries used in data science like Numpy, Pandas, Mathplotlib, etc.
• Learned how to observe a dataset and analyse it. Got an insight on how to pre‑process the dataset effectively like when to scale/standardize data for a model, how to deal with highly corelated features, when to label encode and when to one‑hot encode etc.
• Learned and implemented different Regression, Classification and Clustering models; learned linear models like Linear, Ridge and Lasso Regression and non‑linear models like KNN, SVR, Naive Bayes, Random Forest and LightGBM.
• Implemented everything learned in a Hackathon hosted on Zindi.

For the implementataion assignments, head to the github repo.