Stanford MLSys Seminar Series is a seminar series on the frontier of machine learning and systems. Its 2025 "Hidden Layer" series schedule lists talks, and earlier limited series covered systems for machine learning and foundation models. Stanford students could sign up for associated classes, and an email list provides speaker and livestream notifications.
StepByStepML provides free online machine learning calculators that solve algorithms step-by-step for computer science exams. Users input a dataset and the site shows the full manual calculation for algorithms including K-Means, Minimax, KNN, A* Search, and evaluation metrics. Theory guides accompany the interactive solvers, and the site states it is built for CS students.
I am trask is a machine learning craftsmanship blog. Posts listed include Decentralized AI in 50 Lines of Python, Is the Universe Random?, Safe Crime Detection, Deep Learning without Backpropagation and Building Safe A.I.
mlpack is a header-only C++ machine learning library with bindings to Python, Julia, R, Go, and the command line. It is built on Armadillo, ensmallen, and cereal and provides implementations of machine learning algorithms. The documentation lists classification, regression, clustering, and preprocessing facilities. It is open source under the 3-clause BSD license.
MLU-Explain is an education initiative from Amazon that teaches machine learning concepts through visual essays. It publishes interactive articles on topics such as neural networks, logistic regression, reinforcement learning, ROC and AUC, cross-validation, random forests, and decision trees.
mexopencv is a collection and development kit of MATLAB MEX functions for the OpenCV library. It provides MATLAB MEX functions interfacing a hundred OpenCV APIs and includes a C++ class converting between MATLAB and OpenCV data types. The package is intended for fast prototyping of OpenCV applications in MATLAB and for developing custom MEX functions.
ShopPal is a U.S.-based company providing AI infrastructure integration, operational enablement and go-to-market execution services for fashion and apparel brands. Its services cover shopping agent integration, AI system implementation and operations, and AI-assisted content and campaign execution.
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StepByStepML provides free online machine learning calculators that solve algorithms step-by-step for computer science exams. Users input a dataset and the site shows the full manual calculation for algorithms including K-Means, Minimax, KNN, A* Search, and evaluation metrics. Theory guides accompany the interactive solvers, and the site states it is built for CS students.
I am trask is a machine learning craftsmanship blog. Posts listed include Decentralized AI in 50 Lines of Python, Is the Universe Random?, Safe Crime Detection, Deep Learning without Backpropagation and Building Safe A.I.
mlpack is a header-only C++ machine learning library with bindings to Python, Julia, R, Go, and the command line. It is built on Armadillo, ensmallen, and cereal and provides implementations of machine learning algorithms. The documentation lists classification, regression, clustering, and preprocessing facilities. It is open source under the 3-clause BSD license.
MLU-Explain is an education initiative from Amazon that teaches machine learning concepts through visual essays. It publishes interactive articles on topics such as neural networks, logistic regression, reinforcement learning, ROC and AUC, cross-validation, random forests, and decision trees.
mexopencv is a collection and development kit of MATLAB MEX functions for the OpenCV library. It provides MATLAB MEX functions interfacing a hundred OpenCV APIs and includes a C++ class converting between MATLAB and OpenCV data types. The package is intended for fast prototyping of OpenCV applications in MATLAB and for developing custom MEX functions.
ShopPal is a U.S.-based company providing AI infrastructure integration, operational enablement and go-to-market execution services for fashion and apparel brands. Its services cover shopping agent integration, AI system implementation and operations, and AI-assisted content and campaign execution.
