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

ML notes. Feel free to explore
https://github.com/adnaaaen/machine-learning-notes

fundamentals machine-learning-models model-evaluation-and-selection model-implementation

Last synced: 4 months ago
JSON representation

ML notes. Feel free to explore

• Host: GitHub
• URL: https://github.com/adnaaaen/machine-learning-notes
• Owner: adnaaaen
• License: mit
• Created: 2024-11-10T10:37:35.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-12-30T06:47:13.000Z (5 months ago)
• Last Synced: 2024-12-30T07:35:25.217Z (5 months ago)
• Topics: fundamentals, machine-learning-models, model-evaluation-and-selection, model-implementation
• Language: Jupyter Notebook
• Homepage:
• Size: 623 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
Welcome to my **Machine Learning Notes** repository! 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 **Linear Regression** 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/)