MT-205 Probability and Statistics for Computer Science

Overview

This repository is dedicated to the study and application of probability and statistics within the field of Computer Science. It covers common discrete and continuous distributions, their applications in decision and estimation problems, and statistical methods for data analysis.

Contents

• Ass: Assignments and solutions related to statistical concepts.
• book: Reference materials and textbooks.
• 01-intro-to-data-f20.pdf to 03-variance-f20.pdf: Lecture notes on introductory statistics concepts.
• Assignment.ipynb: Jupyter notebook with assignment problems.
• *.ipynb: Series of Jupyter notebooks detailing various statistical distributions and their applications.
• cartoon guide to statistics.pdf: A visual and approachable guide to statistics.
• README.md: Information about this repository.

Topics Covered

• Decision Making with Statistical Functions
• Entropy and Information Theory
• Seaborn and Matplotlib for Data Visualization
• Spam Detection Algorithms
• One-Hot Encoding Techniques

Usage

These resources are beneficial for students enrolled in MT-205 or any individual interested in learning about probability and statistics in computer science. Feel free to clone this repository and explore the materials.

Contributing

Contributions to this repository are welcome! If you have additional resources, corrections, or improvements to the existing materials, please submit a pull request.

License

This project is open-sourced.