AkiRusProd/basic-ml-algorithms
Python implementations of basic machine learning algorithms
This project provides fundamental machine learning algorithms implemented in Python. It takes in datasets and applies common analytical techniques to produce models and predictions. Data scientists, analysts, and students learning machine learning concepts would find this useful for understanding and applying core algorithms.
No commits in the last 6 months.
Use this if you are a data scientist, analyst, or student who needs to implement and understand foundational machine learning algorithms directly in Python for various data analysis tasks.
Not ideal if you need highly optimized, production-ready machine learning libraries with extensive features and support, or if you prefer using pre-built tools rather than writing Python code.
Stars
14
Forks
2
Language
Python
License
—
Category
Last pushed
Feb 17, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/AkiRusProd/basic-ml-algorithms"
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