My tryst with Machine Learning began with a love for Statistics from high school. During my Computer Engineering undergraduate program, I became comfortable with Machine Learning and since then I have worked on several mini-projects which are contained in this repository.
This repository contains X mini projects in Python, R & Spark.
The repository contains mini-projects on the following machine learning techniques:
- Linear Regression - Simple linear regression, multiple linear regression, non-linear transformation of predictors
- Logistic Regression
- Linear & Quadratic Discriminant Analysis
- K-Nearest Neighbour
- Polynomial Regression
- Splines
- GAM
- Decision Trees - Regression, Classification, Bagging, Boosting
- Support Vector Machines
- Principal Component Analysis
- K-means Clustering
- Ensemble Models
- Introduction to Statistical Learning by Gareth James • Daniela Witten • Trevor Hastie • Robert Tibshirani
- Hands on Machine Learning with Scikit Learn & Tensorflow