🚀 30 Machine Learning Projects – From Beginner to Advanced:-

A curated collection of 30 end-to-end Machine Learning projects covering Regression, Classification, Clustering, NLP, Time Series, and Ensemble methods.

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📌 Table of Contents

• Overview
• Project Structure
• Projects List
• Technologies Used
• Installation
• How to Use
• Contributing

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🔍 Overview

This repository contains 30 practical ML projects designed to help you:

✔ Understand ML algorithms with real datasets
✔ Learn data preprocessing, visualization & modeling
✔ Build hands-on experience for jobs & internships
✔ Strengthen ML & Data Science fundamentals

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📂 Project Structure

30-Machine-Learning-Projects
│
├── A-Regression Projects(1-7)
├── B-Classification Projects(8-13)
├── C-Clustering Projects(14-16)
├── D-Association Rule Mining(17-18)
├── E-Ensemble Methods(19-23)
├── F-Natural Language Processing(24-27)
└── G-Time_Series(28-30)

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📊 Projects List

S.No	Project Name	Link
1	House Price Prediction	click here
2	Car Price Prediction	click here
3	Student Score Prediction	click here
4	Salary Prediction	click here
5	Sales Forecasting	click here
6	Gold Price Prediction	click here
7	Medical Insurance Cost Prediction	click here
8	Breast Cancer Detection	click here
9	Email Spam Detection	click here
10	Diabetes Prediction	click here
11	Custoer Churm Prediction	click here
12	Iris Flower Classification	click here
13	Titanic Survival Prediction	click here
14	Customer Segmentation	click here
15	Mall Customers Segmentation	click here
16	Spotify Songs Clustering	click here
17	Market Basket Analysis(Apriori)	click here
18	Movie Pair Recommendation	click here
19	Customer Churm Ensemble Model	click here
20	House Price Ensemble Model	click here
21	Voting Classifier on Iris Dataset	click here
22	Spam Detection Using Ensembles	click here
23	Fraud Detection Using Ensembles	click here
24	Sentiment Analysis	click here
25	Fake News Detection	click here
26	Resume Classification	click here
27	Text Classification(News_Dataset)	click here
28	Daily Temperature Prediction	click here
29	Weather Forecasting	click here
30	Stock Price Trend Prediction	click here

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🛠 Technologies Used

• Python
• NumPy
• Pandas
• Matplotlib & Seaborn
• XGBoost
• Ensemble Learning
• Scikit-Learn
• NLP Libraries
• Jupyter Notebook
• Hypertuning & Optimization Techniques

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⚙️ Installation

git clone https://github.com/ash-iiiiish/30-Machine-Learning-Projects
cd 30-Machine-Learning-Projects
pip install -r requirements.txt

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▶️ How to Use

1. Navigate to any project folder
2. Open the Jupyter Notebook
3. Run cells step-by-step

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👨‍💻 Contributors

• @ash-iiiiish

🤝 Contributing

Contributions are welcome! Fork this repository and submit a pull request.