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This repository contains the projects and code I developed during my machine learning internship at Prodigy Infotech. The work focuses on applying machine learning techniques to solve real-world problems, leveraging tools like Python, Numpy, Pandas, and scikit-learn.

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I want to express my heartfelt thanks for the incredible opportunity to intern at Podigy Infotech. This experience has been invaluable in helping me grow my skills in machine learning and gain practical knowledge.I hope to stay in touch and contribute to similar innovative projects in the future. Thank you once again for this wonderful experience.

📝Overview

This repository showcases my work during my machine learning internship at Prodigy Infotech. The projects include end-to-end machine learning workflows, from data preprocessing and exploratory data analysis (EDA) to model training, evaluation, and visualization.

📂 Repository Contents

notebooks: Contains Jupyter notebooks detailing data analysis, modeling, and visualizations.

datasets: Includes sample datasets used for the projects.

PRODIGY_ML_01

#Task-01

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

Dataset Used:- https://www.kaggle.com/c/house-prices-advanced-regression-techniques/data

PRODIGY_ML_02

#Task-02

Create a K-means clustering algorithm to group customers of a retail store based on their purchase history.

Dataset Used:- https://www.kaggle.com/datasets/vjchoudhary7/customer-segmentation-tutorial-in-python

🤝 Connect With Me If you have any questions or want to collaborate, feel free to reach out!

LinkedIn: www.linkedin.com/in/dhanashri-patil24

Email: [email protected]

About

This repository contains the projects and code I developed during my machine learning internship at Prodigy Infotech. The work focuses on applying machine learning techniques to solve real-world problems, leveraging tools like Python, Numpy, Pandas, and scikit-learn.

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