Welcome to the repository! 🚀
This repository is a collection of various machine learning and deep learning algorithms implemented in Python, presented in a modular format. Our aim is to bridge the gap between theoretical knowledge and practical implementation by providing a comprehensive resource of classical and commonly used models.
This project is maintained by the students of NITK CDS (Computational and Data Science) Batch of 2025. We believe in the power of collaborative learning and are committed to making this repository a valuable asset for both beginners and experienced practitioners in the field of machine learning and data science.
In the world of machine learning and data science, there is a significant emphasis on understanding theories and algorithms. However, we often find a gap when it comes to applying these theories to real-world problems. "Deeper Learning" aims to reverse this trend by bringing models to the data, making it easier for individuals to implement and experiment with various algorithms.
We welcome contributions from the community! Whether you are a student, researcher, or industry professional, your expertise and insights can help enhance the repository. Feel free to contribute by adding new models, improving existing ones, or providing documentation enhancements.
To contribute, follow these steps:
- Fork the repository.
- Create a new branch for your changes.
- Make your modifications and improvements.
- Test your changes thoroughly.
- Submit a pull request. Please ensure that your contributions adhere to our code of conduct.
Each algorithm and model is organized in a modular format, making it easy for you to understand, implement, and experiment with. We encourage you to explore them and try them out on your own datasets.
Follow the documentation provided with each model for implementation details and usage instructions.
Happy learning and modeling! 🤖✨