Supports teaching, studying or skills practice with AI-guided learning tools.
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.
Generative AI Explained by NVIDIA is an educational course offered by NVIDIA focused on generative AI. The course includes learning objectives, a list of covered topics, a full course outline, and related training resources. It provides public virtual workshop options structured as six 2-hour sessions, and offers private team or individual training upon request.
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 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.
Microsoft Azure for Students offers access to cloud services, developer tools and $100 in Azure credits for students to build apps and explore AI and data science. Signup uses a school email, renews yearly while the user is a student, and does not require a credit card.
Full Stack Deep Learning offers news, community, and courses for people building AI-powered products. It covers the lifecycle of an AI-powered product, from defining the problem and picking a GPU or foundation model to production deployment and continual learning.
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
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.
Generative AI Explained by NVIDIA is an educational course offered by NVIDIA focused on generative AI. The course includes learning objectives, a list of covered topics, a full course outline, and related training resources. It provides public virtual workshop options structured as six 2-hour sessions, and offers private team or individual training upon request.
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 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.
Microsoft Azure for Students offers access to cloud services, developer tools and $100 in Azure credits for students to build apps and explore AI and data science. Signup uses a school email, renews yearly while the user is a student, and does not require a credit card.
Full Stack Deep Learning offers news, community, and courses for people building AI-powered products. It covers the lifecycle of an AI-powered product, from defining the problem and picking a GPU or foundation model to production deployment and continual learning.
