milaan9/Machine_Learning_Algorithms_from_Scratch
This repository explores the variety of techniques and algorithms commonly used in machine learning and the implementation in MATLAB and PYTHON.
This project helps machine learning practitioners understand the inner workings of various machine learning algorithms. It provides practical implementations in MATLAB and Python, allowing users to see how common techniques like Decision Trees, Naive Bayes, and K-Means Clustering are built from the ground up. The output is a deeper conceptual understanding and runnable code examples.
194 stars. No commits in the last 6 months.
Use this if you are a machine learning student or practitioner who wants to learn the fundamental concepts and code implementations of core machine learning algorithms.
Not ideal if you are looking for a high-level library to quickly apply pre-built machine learning models to your data without delving into their internal mechanisms.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Dec 09, 2022
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