Table of Contents

1. Introduction
2. Prerequisites
3. Setup Instructions
4. Usage
5. Directory Description

Introduction

This repository contains implementations of various Machine Learning algorithms, including the Perceptron Learning Algorithm, Pocket Algorithm, Linear Regression, Neural Network, and Support Vector Machines.

Prerequisites

Basic understanding of all the algorithms mentioned above.

Setup Instructions

Ensure that Python is installed on your system, and also make sure to install the following libraries: numpy, pandas, keras, scikit-learn, and tensorflow. Additionally, have a tool installed to open Python notebook (ipynb) files.

Usage

Navigate to each algorithm's folder and refer to the accompanying specification PDF for detailed instructions on running the code and understanding the implementation.

Directory Description

Perceptron Learning Algorithm - PLA and Pocket Algorithm

This folder includes the Perceptron learning algorithm and the Pocket algorithm, which are basic machine learning algorithms.

Caption: Basic Perceptron Learning Algorithm

Caption: Basic Pocket Algorithm with Learning Rate

Caption: PLA with Learning Rate

Comparing PLA, Pocket and Linear Regression

Explore this folder to compare PLA, Pocket, and Linear Regression algorithms. We also experiment with 3rd order transformations to analyze their impact on results.

Caption: Comparison in 2D

Caption: Comparison in 3D

Neural Network

This directory contains the implementation of neural networks.

Support Vector Machine

Find the implementation of Support Vector Machine in this directory.