Welcome to the Machine Learning Examples Repository! This repository contains a collection of Jupyter notebooks showcasing various machine learning techniques, including classification, regression, and more. Each example is accompanied by the necessary datasets to replicate and experiment with the provided code.
This repository serves as a learning resource for machine learning enthusiasts, providing hands-on examples and practical implementations. Whether you are a beginner or an experienced practitioner, you can explore and experiment with different machine learning concepts by diving into the Jupyter notebooks available here.
The repository is organized as follows:
- classification: Jupyter notebooks demonstrating various classification algorithms.
- regression: Jupyter notebooks illustrating regression techniques.
- clustering: Examples showcasing different clustering algorithms.
- datasets: Datasets used in the examples, organized by category.
To get started, follow these steps:
-
Clone this repository to your local machine:
git clone https://github.com/aliemami-coder/machine-learning-examples.git
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Navigate to the desired example directory (e.g.,
classification) and open the corresponding Jupyter notebook. -
Run the notebook cell by cell to understand the implementation and experiment with the code.
- Example 1: KNN
- comming soon...
comming soon...
If you would like to contribute to this repository, feel free to submit pull requests. Contributions may include adding new examples, improving existing code, or suggesting enhancements.
This repository is licensed under the MIT License. Feel free to use the code and examples for educational and non-commercial purposes.