amitkaps/hackermath
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
This project helps data professionals understand and apply essential mathematical and statistical concepts directly in practical machine learning scenarios. It takes core ideas from linear algebra and statistics, and rather than focusing on theoretical proofs, demonstrates their usage through code. It's designed for programmers and data analysts who want to deepen their understanding of data science's underlying math.
1,461 stars. No commits in the last 6 months.
Use this if you have programming experience and want to learn the mathematics behind data science and machine learning through practical coding examples.
Not ideal if you prefer a purely theoretical, proof-based approach to learning mathematics or if you do not have basic programming skills.
Stars
1,461
Forks
282
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Nov 26, 2017
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/amitkaps/hackermath"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
tiagomonteiro0715/The-Math-Behind-Artificial-Intelligence-A-Guide-to-AI-Foundations
A book on the mathematical foundations of AI from an engineering perspective.
jonkrohn/ML-foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
hrnbot/Basic-Mathematics-for-Machine-Learning
The motive behind Creating this repo is to feel the fear of mathematics and do what ever you...
Visualize-ML/Book5_Essentials-of-Probability-and-Statistics
Book_5_《统计至简》 | 鸢尾花书：从加减乘除到机器学习；上架！
Visualize-ML/Book7_Visualizations-for-Machine-Learning
Book_7_《机器学习》 | 鸢尾花书：从加减乘除到机器学习；欢迎批评指正