A Repository Containing Classification, Clustering, Regression, Recommender Notebooks with illustration to make them.
Dataiku is described as a platform for AI success that unites people, orchestration, and governance. It brings analytics, models, and AI agents together in a single governed system, with centralized routing, quotas, monitoring, and safety controls for managing LLM providers.
A guide to MLOps is an open-source tutorial from the Swiss AI Center team that walks engineers and small teams from notebook experiments to production. It covers local training and model evaluation, moving the model to the cloud, serving and deploying, monitoring and maintaining, and labeling data and retraining, using tools such as DVC, Git, GitHub Actions, CML, Docker, BentoML, Fluent Bit, Evidently AI, and Label Studio.
LearnClash is a quiz duel app in which players face a real opponent 1v1 on general knowledge or a chosen topic. Every answer is explained, and missed questions return after 7 days. Duels are turn-based with a 72-hour window per turn. Duels, explanations and missed-question reviews are free, with no ads.
An MIT OpenCourseWare course covering matrix theory and linear algebra, emphasizing topics useful in physics, economics, social sciences, natural sciences and engineering. It is designed for independent study and includes lecture videos by Gilbert Strang, summary notes, problem solving videos, and problem sets with solutions.
Made With ML is an educational resource by Anyscale that teaches how to responsibly design, develop, deploy and iterate on production machine learning applications. Its lessons cover design, data preparation, model training, development, testing, reproducibility and production.
An interactive tutorial and introduction to programming with Python for the humanities by Folgert Karsdorp. The book has 10 chapters covering text processing, preprocessing, programming principles, readability computation, authorship attribution, object-oriented programming, information retrieval, a PDF search web application, classification and hierarchical clustering. It expects no prior programming experience. Chapters 5 and 6 are in draft status.
Community notes
Be the first to share how this project worked for you.
Sign in with a verified account to leave a review or join the discussion.
Sign in to reviewKeep exploring
Dataiku is described as a platform for AI success that unites people, orchestration, and governance. It brings analytics, models, and AI agents together in a single governed system, with centralized routing, quotas, monitoring, and safety controls for managing LLM providers.
A guide to MLOps is an open-source tutorial from the Swiss AI Center team that walks engineers and small teams from notebook experiments to production. It covers local training and model evaluation, moving the model to the cloud, serving and deploying, monitoring and maintaining, and labeling data and retraining, using tools such as DVC, Git, GitHub Actions, CML, Docker, BentoML, Fluent Bit, Evidently AI, and Label Studio.
LearnClash is a quiz duel app in which players face a real opponent 1v1 on general knowledge or a chosen topic. Every answer is explained, and missed questions return after 7 days. Duels are turn-based with a 72-hour window per turn. Duels, explanations and missed-question reviews are free, with no ads.
An MIT OpenCourseWare course covering matrix theory and linear algebra, emphasizing topics useful in physics, economics, social sciences, natural sciences and engineering. It is designed for independent study and includes lecture videos by Gilbert Strang, summary notes, problem solving videos, and problem sets with solutions.
Made With ML is an educational resource by Anyscale that teaches how to responsibly design, develop, deploy and iterate on production machine learning applications. Its lessons cover design, data preparation, model training, development, testing, reproducibility and production.
An interactive tutorial and introduction to programming with Python for the humanities by Folgert Karsdorp. The book has 10 chapters covering text processing, preprocessing, programming principles, readability computation, authorship attribution, object-oriented programming, information retrieval, a PDF search web application, classification and hierarchical clustering. It expects no prior programming experience. Chapters 5 and 6 are in draft status.
