pmuens/lab
Research Environment to play around with Algorithms and Data (Structures)
This project provides clear, step-by-step explanations and functional examples of fundamental machine learning algorithms. It helps anyone learning about these concepts by showing how they work internally, taking raw data and illustrating the logical outputs of models like linear regression or decision trees. It's ideal for students, data science beginners, or educators who want to understand the core mechanics without relying on complex libraries.
No commits in the last 6 months.
Use this if you are learning or teaching the foundational principles of machine learning algorithms and want to see transparent, easy-to-understand code implementations.
Not ideal if you need high-performance tools for production-level data analysis or sophisticated model building, as the focus here is on educational clarity over speed.
Stars
56
Forks
7
Language
Jupyter Notebook
License
—
Category
Last pushed
Aug 13, 2020
Commits (30d)
0
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