This repository contains a collection of machine learning models applied to various datasets, subjects, and problem types. It serves as a comprehensive resource for learning and experimenting with different machine learning techniques and algorithms.
The datasets used in this repository include:
- Mall Customers - To draw relations between annual income and spending score.
- Movie - Movie reviews for sentiment analysis.
- Laptop - Gauge price changes for various laptop specifications.
- Diabetes - To understand influence of factors such as insulin, blood pressure, skin thickness, etc. on diabetic/non-diabetic individuals.
- SONAR - Assess a given substance to determine whether it is a rock or a mine based on the parameters present in the dataset.
The repository contains implementations of various machine learning models, such as:
- Linear Regression
- Logistic Regression
- Support Vector Machines (SVM)
- K-Nearest Neighbors (KNN)
- Decision Trees
- Random Forests
- K-Means Clustering
Ensure you have Python 3.7+ installed. Install the required dependencies using pip:
pip install -r requirements.txt