Machine Learning Projects

This repository contains various machine learning projects implemented using Python. The projects explore different algorithms and techniques, including K-Nearest Neighbors, Logistic Regression, Multi-Layer Perceptron, and applications in Regression and Natural Language Processing.

Projects Overview

1. K-Nearest Neighbour

• Implementation of the K-Nearest Neighbors algorithm for classification tasks.
• File: K_Nearest_Neighbour.py

2. Logistic Regression

• Task/Problem Statement: Solve multi-class classification problems using the Logistic Regression model and visualize errors.
• Dataset: winequality-white.csv for wine quality prediction.
• File: Logistic_Regression.py

3. Multi Layer Perceptron

• Task/Problem Statement: Solve multi-class classification problems using the Multi-Layer Perceptron (MLP) model.
• Dataset: MNIST dataset for handwritten digit classification.
• File: Multi_Layer_Perceptron.py

4. Regression & Natural Language Processing

• Task/Problem Statement: Solve regression and classification problems using numeric and text data.
• Dataset: EnergyEfficiency.xlsx for energy analysis.
• File: Regression_NLP.py

Installation

To run the notebooks, ensure you have Python and Jupyter Notebook installed. You can install the required packages using pip:

pip install numpy pandas scikit-learn matplotlib keras openpyxl