moon-hotel/MachineLearningWithMe
A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@月来客栈 出品
This is a comprehensive learning resource for common machine learning algorithms. It provides explanations, implementations, and video tutorials for various statistical models. Anyone interested in understanding how machine learning algorithms work and applying them to solve real-world problems will find this beneficial.
283 stars.
Use this if you are a student or practitioner who wants to learn the fundamental principles and practical implementations of popular machine learning algorithms.
Not ideal if you are looking for a plug-and-play solution or an advanced research-oriented toolkit for cutting-edge deep learning.
Stars
283
Forks
50
Language
Jupyter Notebook
License
—
Category
Last pushed
Jan 17, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/moon-hotel/MachineLearningWithMe"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
uxlfoundation/scikit-learn-intelex
Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
INRIA/scikit-learn-mooc
Machine learning in Python with scikit-learn MOOC
ddbourgin/numpy-ml
Machine learning, in numpy
nubank/fklearn
fklearn: Functional Machine Learning
gavinkhung/machine-learning-visualized
ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy