https://github.com/mohammadreza-mohammadi94/ml_algorithms_from_scratch
Machine Learning algorithms and metrics implemented from scratch to deepen understanding, including Linear Regression, Decision Trees, Precision, Recall, and more—coded without ML libraries
https://github.com/mohammadreza-mohammadi94/ml_algorithms_from_scratch
machine-learning machine-learning-algorithms
Last synced: 2 months ago
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Machine Learning algorithms and metrics implemented from scratch to deepen understanding, including Linear Regression, Decision Trees, Precision, Recall, and more—coded without ML libraries
- Host: GitHub
- URL: https://github.com/mohammadreza-mohammadi94/ml_algorithms_from_scratch
- Owner: mohammadreza-mohammadi94
- Created: 2024-11-17T11:43:16.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-11-23T14:28:10.000Z (6 months ago)
- Last Synced: 2025-01-24T15:42:04.524Z (4 months ago)
- Topics: machine-learning, machine-learning-algorithms
- Language: Python
- Homepage:
- Size: 28.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ML Algorithms From Scratch
This repository contains implementations of various **Machine Learning algorithms** developed from scratch using Python. The primary goal is to understand the inner workings of these algorithms by coding them manually, without relying on pre-built libraries like Scikit-learn for the core computations.
---
## Table of Contents
- [Algorithms Implemented](#algorithms-implemented)
- [Features](#features)
- [Usage](#usage)
- [Contributing](#contributing)
- [Author](#author)
---
## Algorithms Implemented
The repository includes the following algorithms:
- Linear Regression
- Logistic Regression
- Decision Tree
- K-Nearest Neighbors (KNN)
- Support Vector Machine (SVM)
- K-Means Clustering
- Gradient Descent
- Naive Bayes
- Principal Component Analysis (PCA)
---
## Features
- **Pure Python Implementations:** No reliance on ML libraries for algorithm logic.
- **Educational Focus:** Emphasizes understanding the fundamentals.
- **Extensible Code:** Easy to modify and adapt for experimentation.
---
## Usage
1. Clone the repository:
```bash
git clone https://github.com/mohammadreza-mohammadi94/ML_Algorithms_From_Scratch.git
cd ML_Algorithms_From_Scratch
```
2. Explore the code for individual algorithms located in the respective subdirectories.
3. Run the scripts directly to test their functionality
---
## Contributing
Contributions are welcome! If you'd like to add new algorithms or improve existing ones:
1. Fork the repository.
2. Create a new branch for your feature.
3. Submit a pull request.
---
This repository serves as a learning resource for anyone interested in understanding Machine Learning algorithms at a deeper level.