Welcome to the ML-Study-Jam repository, a collaborative learning initiative organized by the TensorFlow User Group Durg. This repository is designed to support participants through various stages of their machine learning journey, from basics to more advanced topics.
The ML-Study-Jam is a structured learning program that includes:
- Hands-on Assignments: Practical exercises and projects.
- Tutoring Sessions: Guidance and support from experienced mentors.
- Tech Talks: Expert sessions to deepen your understanding.
- Group Discussions: Collaborative learning with peers.
The repository is organized into different folders corresponding to the various sessions and days of the study jam:
- Day-1 Intro to Python and Numpy: Basics of Python programming and an introduction to Numpy.
- Day-2 Pandas: Data manipulation and analysis using Pandas.
- Day-3 Math Club: Foundational mathematics for machine learning.
- Day-4 Intro to ML: Core concepts and techniques in machine learning.
- Day-5 Linear Regression: Detailed study and implementation of linear regression.
Each folder contains Jupyter notebooks and other resources to help you follow along with the sessions.
To get started with the ML-Study-Jam:
- Clone the Repository:
git clone https://github.com/TFUG-Durg/ML-Study-Jam.git
- Navigate to the Repository:
cd ML-Study-Jam - Install Required Packages:
Ensure you have the necessary Python packages installed. You can install them using pip:
pip install -r requirements.txt
- Run Jupyter Notebooks:
Launch Jupyter Notebook to start working on the provided notebooks:
jupyter notebook
We welcome contributions! If you'd like to contribute, please fork the repository and submit a pull request. For major changes, please open an issue first to discuss what you would like to change.
This project is licensed under the MIT License.
For more information or if you have any questions, please reach out to the TensorFlow User Group Durg community through our official page.
Join us in this exciting journey to master machine learning with practical, hands-on experience. Happy learning!
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