DML-OpenProblem is an open-source repository of problems focused on linear algebra, machine learning, and deep learning. The problems are designed to be solved from scratch, providing a robust learning experience. This project powers the website Deep-ML.
To get started with DML-OpenProblem, clone the repository and install the necessary dependencies.
git clone https://github.com/yourusername/DML-OpenProblem.git
cd DML-OpenProblem
pip install -r requirements.txt
You can use the repository to create, edit, and solve problems related to linear algebra, machine learning, and deep learning. The problems are structured in directories, each containing relevant files such as learn.html for the learning section and solution.py for the solution code.
To launch the Streamlit application for editing and viewing problems, use the following command:
streamlit run app.py
DML-OpenProblem/
│
├── Problems/
│ ├── 1_matrix_times_vector/
│ │ ├── learn.html
│ │ └── solution.py
│ ├── 2_transpose_matrix/
│ │ ├── learn.html
│ │ └── solution.py
│ └── ... (additional problem directories)
│
├── app.py
├── requirements.txt
└── README.md
learn.html
: HTML file containing the learning section with explanations and examples.solution.py
: Python file containing the solution to the problem along with tests.We welcome contributions to improve DML-OpenProblem and deep-ml.com. If you have a new problem to add or improvements to existing problems, please fork the repository and submit a pull request. All contributions will be displayed on deep-ml.com. For example, check out this problem: Divide Dataset Based on Feature Threshold. A helpfull tool to work on the learn section and know what it would look like on the front end is https://openproblem-r4vsjwuthdl9a3qzrd4p3m.streamlit.app/.
This project is for educational reasons only. See the LICENSE file for details.