nekosilverfox/Machine-learning
🔬 深度å¦ä¹ 项目库 —— 基于 sklearn
This project provides practical examples and code for applying machine learning to real-world problems. It helps users understand and implement solutions for tasks like predicting sales, classifying customers, detecting objects in images, or categorizing text. Anyone who needs to make predictions or find patterns in data—such as business analysts, data scientists, or researchers—would find this useful.
No commits in the last 6 months.
Use this if you are a practitioner looking for clear examples and code to solve prediction, classification, or clustering problems across various domains like sales forecasting, image recognition, or natural language processing.
Not ideal if you are looking for an in-depth theoretical textbook or want to build machine learning algorithms from scratch.
Stars
17
Forks
3
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Apr 14, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/nekosilverfox/Machine-learning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
microsoft/ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
jzsmoreno/likelihood
Code generated from the Machine Learning course to optimization tasks
john-science/scipy_con_2019
Tutorial Sessions for SciPy Con 2019
ethen8181/machine-learning
:earth_americas: machine learning tutorials (mainly in Python3)
x4nth055/pythoncode-tutorials
The Python Code Tutorials