This repository is dedicated to my learnings and assignments from the "Mathematics for Machine Learning" course. It serves as a consolidation of the theoretical knowledge and practical applications of mathematical concepts that underpin machine learning algorithms.
The field of Machine Learning is deeply rooted in mathematics, and this repository reflects my journey through the foundational pillars of linear algebra, calculus, probability, and statistics. Each assignment and project within this repository applies these mathematical frameworks to solve complex problems and build predictive models.
Assignments/: Contains individual directories for each assignment, including Jupyter notebooks, data files, and relevant resources.Notes/: My personal lecture notes and summaries of key mathematical concepts.Projects/: Application of mathematical theories to machine learning projects and case studies.Resources/: Additional resources such as cheat sheets, reference guides, and links to external readings.
Each assignment folder includes:
- A detailed Jupyter notebook that walks through the problem-solving process.
- Data files and any associated materials needed to complete the analysis.
- Visualizations and interpretations that explain the findings in a clear and accessible manner.
Through the assignments and projects in this repository, I have demonstrated the following skills:
- Application of linear algebra in data transformation and model development.
- Use of calculus to understand and optimize machine learning algorithms.
- Implementation of probability and statistics to infer patterns and make predictions from data.
- To follow along with the course material, start with the
Notes/directory. - For practical applications, explore the
Assignments/andProjects/directories. - Feel free to use the
Resources/as a quick reference while studying or working on problems.
I welcome contributions, suggestions, and feedback to improve the content of this repository. If you would like to contribute, please fork the repository and submit a pull request.
This educational material is shared with the community and is licensed under the MIT License.
I would like to thank the instructors and contributors of the "Mathematics for Machine Learning" course for providing the resources and support necessary to advance my understanding of this crucial subject.