This is the Linux app named Coursera Machine Learning whose latest release can be downloaded as CourseraMachineLearningsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Coursera Machine Learning with OnWorks for free.
Suivez ces instructions pour exécuter cette application :
- 1. Téléchargé cette application sur votre PC.
- 2. Entrez dans notre gestionnaire de fichiers https://www.onworks.net/myfiles.php?username=XXXXX avec le nom d'utilisateur que vous voulez.
- 3. Téléchargez cette application dans ce gestionnaire de fichiers.
- 4. Démarrez l'émulateur en ligne OnWorks Linux ou Windows en ligne ou l'émulateur en ligne MACOS à partir de ce site Web.
- 5. Depuis le système d'exploitation OnWorks Linux que vous venez de démarrer, accédez à notre gestionnaire de fichiers https://www.onworks.net/myfiles.php?username=XXXXX avec le nom d'utilisateur que vous souhaitez.
- 6. Téléchargez l'application, installez-la et exécutez-la.
CAPTURES D'ÉCRAN:
Apprentissage automatique sur Coursera
DESCRIPTION:
CourseraMachineLearning is a personal collection of resources, notes, and programming exercises from Andrew Ng’s popular Machine Learning course on Coursera. It consolidates lecture references, programming tutorials, test cases, and supporting materials into one repository for easier review and practice. The project highlights fundamental machine learning concepts such as hypothesis functions, cost functions, gradient descent, bias-variance tradeoffs, and regression models. It also organizes week-by-week course schedules with links to exercises, lecture notes, and additional resources. Alongside the official coursework, the repository includes supplemental explanations, code snippets, and references to recommended textbooks and external materials. By gathering course-related resources into a single space, this project acts as a practical study companion for learners revisiting or supplementing the original course.
Comment ça marche
- Consolidated notes and resources from Andrew Ng’s Coursera ML course
- Programming exercise tutorials and test cases for Octave/MATLAB
- Week-by-week schedule of lectures and assignments
- Covers key ML concepts: regression, logistic regression, neural networks, SVMs, clustering, and recommender systems
- Additional references including online books and lecture notes from CS229
- Supplemental examples and explanations for self-study
Langage de programmation
MATLAB
Catégories
This is an application that can also be fetched from https://sourceforge.net/projects/coursera-machine-learn.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.