🚀 Machine Learning Starter Projects

From Curiosity to Building Real ML Models

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🌱 How It Started

As a first-year B.Tech CSE (AI) student, I didn’t want to just learn Machine Learning — I wanted to build with it.

Instead of waiting for advanced topics, I started early by asking:

“Can I make a machine predict something useful?”

This repository reflects my journey from learning basics → building models → making predictions.

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🧠 Tech Stack

• Python
• NumPy
• Scikit-learn
• Matplotlib

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📌 Projects

📊 Exam Marks Predictor

• Linear Regression model
• Predicts marks based on study hours
• Visualizes data using graphs

What I learned:

• Model training and prediction
• Data visualization
• Understanding relationships in data

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💬 Student Feedback Analyzer (Mini Chatbot)

• NLP-based sentiment classifier
• Uses CountVectorizer + Logistic Regression

Features:

• Takes user feedback
• Predicts Positive / Negative sentiment

What I learned:

• Text preprocessing
• Feature extraction
• NLP basics

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📊 Model Performance

• Regression Model: Shows clear trend between study hours and marks
• NLP Model: Trained on labeled dataset (Positive vs Negative)
• Basic validation performed

(Next step: add accuracy, confusion matrix, etc.)

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🛠️ How to Run

git clone <your-repo-link>
cd <repo-name>

Run the projects:

python marks_predictor.py
python feedback_analyzer.py

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📂 Project Structure

.
├── marks_predictor.py
├── feedback_analyzer.py
├── evenodd.py
└── README.md

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📚 What’s Next

• Advanced ML models
• Real-world datasets
• Deep Learning
• Model deployment (Flask / Streamlit)

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🤝 Let’s Connect

I’m currently learning Machine Learning and AI and open to collaborations and opportunities.

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⭐ If you like this project, consider giving it a star!