A curated directory of university lectures covering deep learning, computer vision, and medical imaging.
Access structured video courses and slides from top universities on machine learning and medical imaging.
Deep Learning Drizzle is an organized directory indexing free university-level lectures, slides, and course materials. It provides direct links to academic courses covering machine learning fundamentals, probabilistic graphical models, computer vision, and medical imaging. Medical AI researchers and clinical coders can use it to build a rigorous theoretical foundation.
The repository categorizes video lectures and slides from institutions like Oxford, Toronto, and Waterloo into distinct topics. It includes dedicated sections for medical imaging, Bayesian deep learning, graph neural networks, and computer vision. Each entry provides links to official course webpages, lecture slides, YouTube playlists, and supplementary code repositories.
This index suits medical professionals, healthcare data scientists, and clinical researchers seeking structured academic coursework in AI and medical image processing. It is not designed for practitioners who need ready-to-use clinical software or pre-trained diagnostic models.
Organizes university AI lectures into structured tables ranging from fundamentals to specialized subjects.
Directly links to university coursework and video series focused on medical image processing.
Connects each listed course to original syllabus pages, lecture slides, and GitHub code repositories.
Spans neural networks, reinforcement learning, graph neural networks, and probabilistic graphical models.
Deep Learning Drizzle is completely free to access on GitHub. The only cost is your own time spent reviewing the linked lecture materials and video courses.
880 open remote AI-training roles, updated November 15, 2026; most pay $20–$175 an hour. Zekai lists them free; the application goes to the employer’s platform.
The repository itself consists of markdown and HTML tables linking to external university course materials, slides, and supplementary code repositories.
Yes, it contains a dedicated section for Medical Imaging courses alongside general computer vision and deep learning subjects.
See Zekai first in Google