This is the Linux app named Stanford Machine Learning Course whose latest release can be downloaded as Stanford-Machine-Learning-Coursesourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Stanford Machine Learning Course
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DESCRIPTION
The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy for learners to navigate and practice. The exercises serve as practical, hands-on reinforcement of theoretical concepts taught in the course. This collection is valuable for students and practitioners who want to strengthen their skills in machine learning through coding exercises.
Features
- Contains programming exercises from Stanford’s Machine Learning course
- Implements algorithms in Python and MATLAB/Octave
- Covers supervised learning methods including regression and classification
- Includes unsupervised learning methods such as clustering and PCA
- Provides neural network training and optimization examples
- Features recommender systems and anomaly detection exercises
Programming Language
MATLAB, Python, Unix Shell
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/stanford-ml.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
