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Machine Learning Internship Projects

Welcome to my Machine Learning Internship Projects repository! This repository contains the projects I completed during my internship. Below, you'll find details about the internship, the tasks I worked on, and the skills I gained.


Internship Offer Letter

Below is my internship offer letter from CodeAlpha:

Internship Offer Letter


Tasks Completed

During my internship, I worked on the following tasks:

  1. Credit Scoring Model

    • Developed a machine learning model to predict credit scores based on customer data.
    • Techniques used: Data preprocessing, feature engineering, and model evaluation.
  2. Emotion Recognition from Speech

    • Built a model to recognize emotions from audio speech data.
    • Techniques used: Audio signal processing, feature extraction, and classification algorithms.
  3. Disease Prediction from Medical Data

    • Created a predictive model to identify diseases based on medical datasets.
    • Techniques used: Data analysis, feature selection, and machine learning algorithms.

Inspiration and Resources

The projects in this repository were inspired by various open-source machine learning projects and datasets available online. I would like to acknowledge the contributions of the machine learning community, which helped me learn and implement these projects effectively.


How to Use This Repository

  1. Clone the repository:
    git clone https://github.com/habibkhan099/Machine-Learning-Internship-Projects.git
    
  2. Navigate to the project folder you're interested in:
    cd Machine-Learning-Internship-Projects/Credit-Scoring-Model
  3. Follow the instructions in the respective project's README file to run the code.

License

This project is licensed under the GNU General Public License v3.0. See the LICENSE file for details.

Thank you for visiting my repository! If you have any questions or feedback, feel free to reach out.

About

This repository contains hands-on Machine Learning projects completed during the CodeAlpha ML Internship (Jan 2025). Projects cover data preprocessing, model training, evaluation, and deployment using Python, Scikit-Learn, TensorFlow, and more. 🌟

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