mlops-course
course22p2
| mlops-course | course22p2 | |
|---|---|---|
| 20 | 6 | |
| 2,741 | 431 | |
| - | 2.6% | |
| 2.1 | 2.0 | |
| 9 months ago | 7 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | 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.
mlops-course
-
Ask HN: Daily practices for building AI/ML skills?
coming from a similar context, i believe going top down might be the way to go.
up to your motivation, doing basic level courses first (as shared by others) and then tackling your own application of the concepts might be the way to go.
i also observe the need for strong IT skills for implementing end-to-end ml systems. so, you can play to your strenghts and also consider working on MLOps. (online self-paced course - https://github.com/GokuMohandas/mlops-course)
i went back to school to get structured learning. whether you find it directly useful or not, i found it more effective than just motivating myself to self-learn dry theory. down the line, if you want to go all-in, this might be a good option for you too.
- [Q] Any good resources for MLOps?
- Open-Source Machine Learning for Software Engineers Course
-
Open-source MLOps Fundamentals Course 🚀
Find all the lessons here → https://madewithml.com/MLOps course repo → https://github.com/GokuMohandas/mlops-courseMade With ML repo → https://github.com/GokuMohandas/Made-With-ML
-
What are examples of well-organized data science project that I can see on Github?
- https://github.com/GokuMohandas/mlops-course (code for MLOps course)
- Made With ML – develop, deploy and maintain production machine learning
-
Where can I learn more about the engineering part of the role?
Haven’t done it but have heard good reviews - https://github.com/GokuMohandas/mlops-course
-
Path to ML from a backend engineering role
If MLOps, read https://github.com/GokuMohandas/mlops-course 😎
- What skills should I focus on to improve as a MLE?
- MadeWithML – A practical approach to learning machine learning
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
What are some alternatives?
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
developer - the first library to let you embed a developer agent in your own app!
mlops-with-vertex-ai - An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI
simpleaichat - Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
TensorRT - PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
playground - Play with neural networks!
machine-learning-interview - Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
latentblending - Create butter-smooth transitions between prompts, powered by stable diffusion
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
machine-learning-specialization-andrew-ng - A collection of notes and implementations of machine learning algorithms from Andrew Ng's machine learning specialization.
fastai - The fastai deep learning library
stylegan2-projecting-images - Projecting images to latent space with StyleGAN2.