This repository contains implementations of various Machine Learning algorithms, including the Perceptron Learning Algorithm, Pocket Algorithm, Linear Regression, Neural Network, and Support Vector Machines.
Basic understanding of all the algorithms mentioned above.
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.
Navigate to each algorithm's folder and refer to the accompanying specification PDF for detailed instructions on running the code and understanding the implementation.
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
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
This directory contains the implementation of neural networks.
Find the implementation of Support Vector Machine in this directory.