Machine Learning Projects

Welcome to the Machine Learning Projects repository! This repository contains a collection of machine learning projects developed using Python and popular libraries such as OpenCV, Pandas, Numpy, and Matplotlib. These projects explore various machine learning techniques and their applications in real-world problems.

Projects Overview

1. Diabetes Testing

• Description: This project uses machine learning algorithms to predict whether a patient has diabetes based on input features such as age, BMI, and glucose levels.
• Tech Stack: Python, Pandas, Numpy, Scikit-Learn
• Key Features: Data preprocessing, model training, accuracy evaluation

2. Housing Price Prediction

• Description: This project uses a regression model to predict housing prices based on various features like location, square footage, and number of bedrooms.
• Tech Stack: Python, Pandas, Numpy, Scikit-Learn
• Key Features: Data cleaning, feature selection, model evaluation

3. Iris Dataset Classification

• Description: The Iris dataset is used to classify flowers into three species based on features like sepal length and petal width.
• Tech Stack: Python, Pandas, Numpy, Scikit-Learn, Matplotlib
• Key Features: Classification algorithms, data visualization, model performance analysis

4. Color Detection

• Description: A computer vision project that detects and classifies colors in images using OpenCV and image processing techniques.
• Tech Stack: Python, OpenCV, Numpy
• Key Features: Image processing, color space conversion, real-time color detection

Technologies Used

• Python: The primary programming language used for the implementation of machine learning models and image processing.
• OpenCV: Used for image processing and computer vision tasks (Color Detection).
• Pandas: For data manipulation and preprocessing tasks.
• Numpy: For handling numerical operations and array manipulations.
• Matplotlib: For data visualization and plotting results.
• Scikit-Learn: For implementing machine learning models like classification and regression.

Getting Started

To get a copy of this repository to run locally on your machine, follow these steps:

Prerequisites

• Python 3.x
• Required libraries (can be installed using requirements.txt)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/machine-learning-projects.git