Machine Learning Projects under Prodigy Infotech

Introduction

Welcome to the Machine Learning Projects repository! This repository contains implementations of various machine learning models for different tasks. Whether you are interested in predicting house prices, clustering retail customers, classifying images of cats and dogs, recognizing hand gestures, or estimating calorie content in food images, this repository has you covered.

Tasks Overview

Task-01: House Price Prediction with Linear Regression

Implement a linear regression model to predict house prices based on square footage, the number of bedrooms, and bathrooms.

Task-02: Retail Customer Clustering with K-means

Create a K-means clustering algorithm to group retail store customers based on their purchase history, providing insights into customer segmentation.

Task-03: Cat and Dog Image Classification with SVM

Implement a Support Vector Machine (SVM) to classify images of cats and dogs from the Kaggle dataset, showcasing image classification skills.

Task-04: Hand Gesture Recognition

Develop a hand gesture recognition model for intuitive human-computer interaction and gesture-based control systems, offering a novel approach to user interaction.

Task-05: Food Recognition and Calorie Estimation

Create a model that accurately recognizes food items from images and estimates their calorie content, empowering users to track their dietary intake and make informed food choices.

Implementation Details

Each task is contained in a separate directory with its respective implementation files. The directory structure is organized as follows:

Task-01_House_Price_Prediction: Linear regression model for predicting house prices.
Task-02_Customer_Clustering: K-means clustering algorithm for retail customer segmentation.
Task-03_Image_Classification_SVM: SVM model for classifying cat and dog images.
Task-04_Hand_Gesture_Recognition: Hand gesture recognition model implementation.
Task-05_Food_Recognition_Calorie_Estimation: Model for recognizing food items and estimating their calorie content.

Usage Instructions

For each task, there are detailed instructions on how to run the code and any additional setup required. Make sure to follow the specific guidelines provided in each task's directory.

Dependencies

The projects use common machine learning libraries such as NumPy, scikit-learn, OpenCV, and Matplotlib. Install the dependencies using the following command:

pip install numpy scikit-learn opencv-python matplotlib

Author

Tapojita Kar - CSE Second Year Undergraduate

Acknowledgments

Special thanks to Prodigy Infotech for providing the internship opportunity and fostering a learning environment.

Thank you reader!

Tapo41/PRODIGY_INFOTECH_ML