This is the Windows app named Machine Learning From Scratch whose latest release can be downloaded as ML-From-Scratchsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
Machine Learning From Scratch
DESCRIPTION:
ML-From-Scratch is an open-source machine learning project that demonstrates how to implement common machine learning algorithms using only basic Python and NumPy rather than relying on high-level frameworks. The goal of the project is to help learners understand how machine learning algorithms work internally by building them step by step from fundamental mathematical operations. The repository includes implementations of algorithms ranging from simple models such as linear regression and logistic regression to more complex techniques such as decision trees, support vector machines, clustering methods, and neural networks. Because the code avoids external machine learning libraries, it exposes the full logic behind model training, optimization, and prediction processes. The project also provides examples and explanations that illustrate how the algorithms behave and how different components interact during training.
Features
- Pure NumPy implementations of machine learning algorithms
- Coverage of models ranging from regression to neural networks
- Educational focus on understanding algorithm internals
- Minimal dependencies without large ML frameworks
- Examples illustrating training and prediction processes
- Readable implementations suitable for studying algorithm mechanics
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/ml-from-scratch.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.