ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Explore the basics of machine learning by implementing various models and algorithms from scratch using Python.
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Free · no card · unsubscribe anytimeMachine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
ML-From-Scratch has 32.3k stars on GitHub. It has been forked 5.4k times. ML-From-Scratch is written mainly in Python. It has been in active development since 2017. ML-From-Scratch is available under the MIT license. Its main topics are data-mining, data-science, deep-learning, deep-reinforcement-learning.
What is ML-From-Scratch?
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Is ML-From-Scratch open source?
ML-From-Scratch is an open-source project. It is released under the MIT license.
Is ML-From-Scratch free?
Yes. ML-From-Scratch is free and open source — you can use, modify and self-host it.
What license does ML-From-Scratch use?
ML-From-Scratch is available under the MIT license.
What language is ML-From-Scratch written in?
ML-From-Scratch is written mainly in Python.
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