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Machine Learning

This repository cotain beginner friendly assignments and projects. Going through these projects will give you an idea how machine learning algorithms do work under the hood. If you also have some beginner friendly projects, please do share.

0. Python Practice

This Python practice is for beginners. It includes all the basic topics and some advance one's are also discussed. It is necessary for those who have just started learning python. It also includes practices for NumPy and all important concepts of it.

1. Information Retrival System (IRS)

In this Assignment/Project assigned by my professor, I have to create a basic type of Search Engine using the vector form of search input. I used NumPy because of it's power and speed. This project has two versions i.e Simple Searching Algorithm, Synonym based Searching Algorithm

2. Linear Regression (Simultaneous Equations)

In this Assignment/Project , I have to code the Linear Regression Model using NumPy. This the implementation of Linear Regression with Simultaneous Equation. It contains Linear, Quadratic, Cubic and upto 6 degree models. I have also measured the accuracy tests and compared each model accuracy.

3. Linear Regression (Gradient Descent)

In this Assignment/Project , I have coded Linear Regression Model using Gradient Descent Algorithm. I also wrote Multiple Linear Regression (MLR) using Gradient Descent.