https://github.com/adnaen/machine-learning-notes

A collection of insightful ML notes 🤖 from my learning journey , 🤗 feel free to explore and learn!
https://github.com/adnaen/machine-learning-notes

learn-machine-learning machine-learning-fundamentals supervised-learning-algorithms

Last synced: about 1 year ago
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A collection of insightful ML notes 🤖 from my learning journey , 🤗 feel free to explore and learn!

• Host: GitHub
• URL: https://github.com/adnaen/machine-learning-notes
• Owner: adnaen
• License: mit
• Created: 2024-11-10T10:37:35.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-21T07:24:21.000Z (about 1 year ago)
• Last Synced: 2025-03-21T08:26:29.296Z (about 1 year ago)
• Topics: learn-machine-learning, machine-learning-fundamentals, supervised-learning-algorithms
• Language: Jupyter Notebook
• Homepage:
• Size: 982 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
This is a living document where I record my learning journey in machine learning. Contributors are welcome to enhance and expand these notes.

I continuously update this repository as I learn more-currently, I’m at the **Tree Based Models** stage.

## Why These Notes

These notes aim to:

- Simplify complex machine learning concepts.

- Provide a step-by-step learning path for aspiring ML enthusiasts.

- Offer Python code implementations from scratch to build a solid understanding of models and algorithms.

> [!NOTE]

> Pre-requisites:

> Before diving into machine learning, make sure you are familiar with essential data skills like:  

>

> - Python

> - Data Analysis

> - Exploratory Data Analysis (EDA)

> - Data Preprocessing

## Learning Path 🚀

1. [**Grasp the Fundamentals**](./fundamentals/)

2. [**Models**](./models/)

3. [**Model Selection**](./model-selection/)

4. [**Model Optimization**](./optimzation/)

5. [**Evaluation Metrics**](./evaluation-metrics/)