This repo contains all the lab assignments written by me for the data science course. It includes implementation of various concepts in using python. It first starts with the Data Visualisation and Statistics of the Data, slowing moving towards the Handling Missing values and the preprocessing of the data. It includes reducing the data and later reconstructing it using PCA from the scratch. Then it move towards the concept of different types of Classifiers(K-Nearest Neighbour Classifier, Bayes Classifier with Unimodal Gaussian Density and Bayes Classifier with Gaussian Mixture Model (GMM)). Then we implement the Linear, Polynomial and Auto Regeression. The final lab is about the different Clustering algorithms.
Each of the lab has a lab report written on it, containing the output results and the discussion about the various conclusions and properties about the data.