arushi-mittal / MDL

Assignments for the Machine, Data, and Learning course at IIIT H (Spring '21). Uses algorithms such as linear regression, genetic algorithms, POMDP, value iteration, and linear programming.

Machine Data and Learning

This repository contains all the assignments done as part of the Machine, Data and Learning course at IIIT Hyderabad (Spring 2021).

Further details about each individual assignment can be found in the README.md and Report.pdf files inside each project directory.

Structure

• Genetic Algorithms: A project involving using genetic algorithms to improve an overfit vector by generalizing it.

• Linear Programming: A linear programming approach to find the best policy for a problem involving path finding.

• Linear Regression: An assignment involving using linear regression to find bias, variance, mean squared error and best fit of a dataset using linear regression.

• POMDP: An assignment involving using POMDP solvers to find the policies and results of a given belief state problem.

• Value Iteration: An assignment involving value iteration to find the optimal path that converges at the given Bellman factor.