https://github.com/faizantkhan/math-for-data-science

Math For Data Science
https://github.com/faizantkhan/math-for-data-science

algorithms csv-files data-science datascience deep-learning engineering library machine-learning machine-learning-algorithms math matplotlib pyth pythonlibrarires statistics trigonometry

Last synced: about 1 month ago
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Math For Data Science

• Host: GitHub
• URL: https://github.com/faizantkhan/math-for-data-science
• Owner: FAIZANTKHAN
• Created: 2024-03-11T19:14:37.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-03-12T19:15:27.000Z (9 months ago)
• Last Synced: 2024-03-12T20:33:29.039Z (9 months ago)
• Topics: algorithms, csv-files, data-science, datascience, deep-learning, engineering, library, machine-learning, machine-learning-algorithms, math, matplotlib, pyth, pythonlibrarires, statistics, trigonometry
• Language: Python
• Homepage:
• Size: 3.07 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Math for Data Science Repository

Overview

Welcome to the Math for Data Science repository! This comprehensive collection of mathematical concepts is curated to empower data scientists with a strong foundation in mathematical principles essential for effective data analysis and interpretation.

Table of Contents

Descriptive Statistics

Mean, Median, Mode

Percentile

Standard Deviation

Mean Absolute Deviation

Probability and Distribution

Normal Distribution

Z Score

Logarithm and Log-Normal Distribution

Trigonometry

Basic Trigonometric Functions

Angles and Degrees

Trigonometric Identities

Hypothesis Testing

Introduction to Hypothesis Testing

Statistical Significance

p-values

Advanced Statistics

Modified Z Score

Advanced Probability Concepts

Central Limit Theorem

Additional Topics

Matrix Operations

Calculus Basics for Data Science

Linear Algebra for Machine Learning

How to Use This Repository

Each topic is organized into its respective directory, containing Jupyter Notebooks, Python scripts, or R code, along with explanatory documentation. Explore the directories to find detailed explanations, code examples, and practical applications.

Getting Started

To get started with this repository, follow these steps:

Clone the Repository:

bash

Copy code

git clone https://github.com/your-username/math-for-data-science.git

Navigate to a Topic:

Browse through the directories to find the specific mathematical concept you want to explore.

Open Jupyter Notebooks:

Open the Jupyter Notebooks or Python scripts to interact with the code and learn through practical examples.

Contributions

Contributions to this repository are highly encouraged. If you have additional topics, improvements, or corrections, please feel free to submit a pull request. Let's collaborate and make this resource even more valuable for the data science community!

Support

If you have any questions, issues, or suggestions, please open an issue on the repository. We welcome feedback and are here to assist you.

Happy learning! 📊✨