GML - Fast-Track to Machine Learning: A Curriculum Crafted for Newbies and Busy Bees
This repository provides a conceptual foundation for understanding the basics of machine learning. It includes key concepts, algorithms, and examples to help beginners grasp the fundamentals of supervised, unsupervised learning, and more. Ideal for those starting their ML journey!
A beginner-friendly introduction to data science and machine learning using Python with libraries like numpy, pandas, and sci-kit learn. The repository includes jupyter notebooks covering python basics, array operations, data visualization, preprocessing, classification, clustering, etc. It also contains implementation of a simple neural network.
Basics y no tan basics de Machine Learning con Python
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