Artificial Intelligence and Machine Learning Repo-1 🤖

Welcome to our AI and Machine Learning Repository!

🚀 Explore the World of AI/ML! This repository is a treasure trove of fascinating AI projects that blend innovation, creativity, and cutting-edge techniques—dive in and be inspired!

We're thrilled to have you here! 🌟

🙌 Maintainers 👩‍💻 :

• Vani Varanya
• Saumya Gupta

🙌 Collaborators :

• Anamika
• Anusha
• Bhavya
• Prachi
• Shanvi

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📂 Project Details

1️⃣ Startup Profit Prediction

👩‍💼 Description:
Predict startup profits based on factors like Expenditure, location, etc. using regression models.

👾 Project Category: Machine Learning

🌟 Details:

• Predicts Startup profits
• Regression models like Linear regression
• Marketing, Administration and R&D Cost, Location data given

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2️⃣ IPL Score Prediction

🏏 Description:
Forecast IPL match scores dynamically using historical player and team performance data.

👾 Project Category: Machine Learning

🌟 Details:

• 13 Cricket Teams
• Regression models like Linear Regression, Random Forest, etc.
• Analysis of IPL Scoring Trends

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3️⃣ Admission Prediction

📚 Description:
Estimate the chances of university admissions based on GRE, TOEFL scores, and other parameters.

👾 Project Category: Machine Learning

🌟 Details:

• Estimates Chances of Admission
• Regression models like Linear Regression
• GRE Score, CGPA, other academic details given

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4️⃣ Emotion Detection

🥹 Description:
Classify text or speech inputs into emotional categories using advanced Natural Language Processing techniques.

👾 Project Category: Machine Learning

🌟 Details:

• Textual data available
• 8 Categories of Emotions : 'Anger', 'Disgust', 'Fear', 'Joy', 'Neutral', 'Sadness', 'Shame', 'Surprise'
• Logistic Regression, Multinomial Naive Bayes, other models

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5️⃣ Credit Card Fraud Detection

💳 Description:
Identify fraudulent credit card transactions using anomaly detection and machine learning classifiers.

👾 Project Category: Machine Learning

🌟 Details:

• Classifies Legit and Fraudulent Transactions
• Logistic Regression and other Classification algorithms

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6️⃣ AirBnB Price Prediction

🏢 Description:
Predict property rental prices on Airbnb based on location, amenities, and historical data.

👾 Project Category: Machine Learning

🌟 Details:

• Property Price Prediction
• Linear Regression and Ensemble learning
• Analysis of Amenities, Location and other Factors

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7️⃣ Sudoku Solver

🔗 Description:
Automatically solve Sudoku puzzles with optimized backtracking and computer vision integration.

👾 Project Category: Python

🌟 Details:

• Interesting Sudoku puzzle solver
• User Friendly TKinter GUI
• Back Tracking Mechanism

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8️⃣ Budget Tracker

🧮 Description:
Develop a tool to monitor and predict expenses, offering personalized financial recommendations.

👾 Project Category: Python

🌟 Details:

• User Friendly UI
• Transaction Tracking
• Report Generation

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9️⃣ Spotify Recommendation

🎙️ Description:
Generate Artist recommendations based on user's past activity and interests of similar users.

👾 Project Category: Machine Learning

🌟 Details:

• Recommendation System for Artists
• LightFM Library
• Matrix Factorization

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🛠️ How to Get Started

1. Fork this Repository
   Click the Fork button to create your copy of this repository.

2. Clone the Repository

   git clone https://github.com/GDG-IGDTUW/AI-ML-1.git  
   cd repo-name  

3. Install Dependencies
   Navigate to the project folder you're interested in.
   For example:

   cd Sentiment-Analysis

   Load the dataset and Install necessary Libraries

4. Make Your Contributions

   • Perform EDA.
   • Train models.
   • Enhance Accuracy.
   • Add features.
   • Test your changes.

5. Submit a Pull Request
   Push your changes and create a pull request to propose your contributions! 🎉

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🤝 Contributing Guidelines

We ❤️ contributions! Follow these simple steps to contribute:

1. Browse through Issues and Choose any
   Browse the Issues tab and comment on the one you'd like to work on.

2. Clone the Repo, Make changes and Branch Out
   Create a new branch for your changes:

   git checkout -b feature-name  

3. Commit Your Work
   Write clear and concise commit messages:

   git commit -m "Add: Feature description"  

4. Push and PR
   Push your branch and create a pull request for review.

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🌟 Tips for Contributors

• Follow the repository’s code style and structure.
• Keep ML model training scripts well-indented and include comments.
• Share any interesting results or insights in the pull request description.
• If you want an issue to be assigned to you, Tag us and mention so under the issue.
• Please be patient and Feel free to Tag the maintainer or collaborators for any queries. ❤️

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Happy Coding and Collaborating!🚀❤️