pabloinsente/math-app-ml
Essential mathematics for applied machine learning and data science
This is a collection of interactive tutorials designed to help you understand the essential mathematical concepts underpinning applied machine learning and data science. It provides clear explanations, visualizations, and Python code examples to demystify topics like linear algebra and calculus. This resource is for anyone looking to build a stronger mathematical foundation for their work in data science or machine learning, particularly those without formal advanced math training.
No commits in the last 6 months.
Use this if you need to grasp the core mathematical principles behind machine learning and data science without getting bogged down in complex proofs, and you learn best through interactive, visual examples.
Not ideal if you already have a strong university-level mathematics background or are looking for highly rigorous, proof-based mathematical textbooks.
Stars
83
Forks
31
Language
Jupyter Notebook
License
—
Category
Last pushed
Jun 22, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/pabloinsente/math-app-ml"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
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...
amitkaps/hackermath
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
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！