Ruban2205/Machine_learning_fundamentals

This repository contains a collection of fundamental topics and techniques in machine learning. It aims to provide a comprehensive understanding of various aspects of machine learning through simplified notebooks. Each topic is covered in a separate notebook, allowing for easy exploration and learning.

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This project helps students and aspiring data scientists understand core machine learning concepts. It provides simplified notebooks that demonstrate how to prepare data, build predictive models for continuous values or categories, and group similar data points. The goal is to offer a hands-on introduction to machine learning workflows, from data exploration to model implementation.

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Use this if you are learning machine learning fundamentals and want to explore practical examples of data preparation and model building.

Not ideal if you are looking for advanced research papers, production-ready code, or a deep dive into highly specialized machine learning subfields.

data-science-education machine-learning-training predictive-modeling-basics data-analysis-fundamentals
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Adoption 4 / 25
Maturity 16 / 25
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Language

Jupyter Notebook

License

MIT

Last pushed

Sep 18, 2023

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