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https://github.com/ali-mhrez/mathematics-of-data-science
A collection of Jupyter Notebooks exploring mathematical concepts and machine learning algorithms relevant to data science, based on the PhD course "Mathematics of Data Science" at the University of Debrecen.
https://github.com/ali-mhrez/mathematics-of-data-science
data-science jupyter-notebook machine-learning probability-theory python
Last synced: 14 days ago
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A collection of Jupyter Notebooks exploring mathematical concepts and machine learning algorithms relevant to data science, based on the PhD course "Mathematics of Data Science" at the University of Debrecen.
- Host: GitHub
- URL: https://github.com/ali-mhrez/mathematics-of-data-science
- Owner: Ali-Mhrez
- Created: 2024-11-03T11:26:59.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-11-13T14:22:22.000Z (3 months ago)
- Last Synced: 2025-01-24T02:15:30.845Z (14 days ago)
- Topics: data-science, jupyter-notebook, machine-learning, probability-theory, python
- Language: Jupyter Notebook
- Homepage:
- Size: 6.16 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Mathematics of Data Science
This repository contains Jupyter Notebooks exploring various mathematical concepts and machine learning algorithms discussed in the PhD course "Mathematics of Data Science" at the University of Debrecen.
## Topics Covered:
- Singular Value Decomposition
- Principal Component Analysis
- Linear/Quadratic Discriminant Analysis
- Naive Bayes
- Kernel Density Estimation
- Support Vector Machines
## Target Audience:
- Data Science Students
- Machine Learning Enthusiasts
## Software/Libraries:
- Python 3.10.12
- NumPy 1.26.4
- Pandas 2.2.2
- Scikit-learn 1.5.2
## Notebooks:
- Kernel Density Estimation (iris dataset)
- Linear Discriminant Analysis vs. Naive Bayes (wdbc dataset)
- Principal Component Analysis (pendigit dataset)
- Singular Value Decomposition (camerman.png)
- Linear/Quadratic Discriminant Analysis (iris dataset)
- Support Vector Machines (synthetic data):
- linearly separable data
- linearly inseparable data
- one vs. one classification strategy
- spambase dataset
## Getting Started:
#### 1. Clone the Repository:
```Bash
git clone https://github.com/Ali-Mhrez/Mathematics-of-Data-Science.git
```
#### 2. Run Notebooks:
Use Jupyter Notebook or JupyterLab to open and execute the notebooks.
## Contributing:
We welcome contributions to this repository! Feel free to submit issues or pull requests.