Hanc1999/Basic-Machine-Learning-Models
A collection for basic machine learning and data mining model implementations, in Python, mainly referencing the books: *Machine Learning: A Probabilistic Perspective* and *Data Mining Concepts and Techniques*. Most codes are implemented in a plain way, without using high-level API or modules. The demo of results is also generally available. Suitable for example and self-learning. Have fun!
This project helps data science students and enthusiasts understand how fundamental machine learning and data mining algorithms work. It provides clear, step-by-step Python code examples for common models like regression, classification, clustering, and association rule mining. You can input sample datasets and see how these algorithms process them to produce insights or predictions.
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Use this if you are learning machine learning and data mining concepts and want to see how the algorithms are implemented from scratch.
Not ideal if you need to build production-ready machine learning applications or require high-performance implementations.
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Jupyter Notebook
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Last pushed
Jul 15, 2021
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