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.
Download and run online this app named Stanford Machine Learning Course with OnWorks for free.
このアプリを実行するには、次の手順に従ってください。
-1。このアプリケーションをPCにダウンロードしました。
--2。ファイルマネージャーhttps://www.onworks.net/myfiles.php?username=XXXXXに必要なユーザー名を入力します。
-3。このアプリケーションをそのようなファイルマネージャにアップロードします。
-4。このWebサイトからOnWorksLinuxオンラインまたはWindowsオンラインエミュレーターまたはMACOSオンラインエミュレーターを起動します。
-5。起動したばかりのOnWorksLinux OSから、必要なユーザー名でファイルマネージャーhttps://www.onworks.net/myfiles.php?username=XXXXXにアクセスします。
-6。アプリケーションをダウンロードし、インストールして実行します。
スタンフォード機械学習コース
Ad
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.
オプション
- 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
プログラミング言語
MATLAB, Python, Unix Shell
カテゴリー
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.