course22p2
machine-learning-specialization-a
| course22p2 | machine-learning-specialization-a | |
|---|---|---|
| 6 | 1 | |
| 431 | - | |
| 2.6% | - | |
| 0.0 | - | |
| 11 days ago | - | |
| Jupyter Notebook | ||
| Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
course22p2
-
Ask HN: Daily practices for building AI/ML skills?
Practical Deep Learning for Coders: https://course.fast.ai/Lessons/part2.html
- Stanford A.I. Courses
-
A quick visual guide to what's actually happening when you generate an image with Stable Diffusion
To me the most important bit is that the diffusion loop turns a noisy latent into an image, does that iteratively, and uses "guidance" in the form of a prompt/controlnet image/etc to do it. The scheduler part, I felt, was needlessly complex for this short explainer, so I hand-wave it away. IF someone wants to dive in deeper, much deeper, they can go through the same thing I'm doing, which is this: https://course.fast.ai/Lessons/part2.html
- Practical Deep Learning for Coders - Part 2 overview
-
Courses for an AI beginner
They also recently released a course for more experienced students where they teach you to implement the Stable Diffusion algorithm from scratch.
-
From Deep Learning Foundations to Stable Diffusion (Part 2)
The full transcripts are available here in plain text form:
https://github.com/fastai/course22p2/tree/master/summaries
machine-learning-specialization-a
-
Stanford A.I. Courses
I recently completed the specialization with Andrew Ng and think it’s a fantastic introduction to ML. It has a good blend of theory, practical tips, and coding.
If anyone is interested, I’ve published detailed notes and my submissions for the lab assignments:
https://github.com/pmulard/machine-learning-specialization-a...
What are some alternatives?
developer - the first library to let you embed a developer agent in your own app!
machine-learning-specialization-andrew-ng - A collection of notes and implementations of machine learning algorithms from Andrew Ng's machine learning specialization.
simpleaichat - Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
playground - Play with neural networks!
latentblending - Create butter-smooth transitions between prompts, powered by stable diffusion
stylegan2-projecting-images - Projecting images to latent space with StyleGAN2.
StableDiffusion-By-Parts - Slice and dice the Stable Diffusion pipeline, saving to a TIFF file in between sections.
simonwillisonblog - The source code behind my blog