Made-With-ML
mlops-with-vertex-ai
| Made-With-ML | mlops-with-vertex-ai | |
|---|---|---|
| 51 | 2 | |
| 35,702 | 327 | |
| - | 1.5% | |
| 6.8 | 0.0 | |
| 5 months ago | 12 months 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.
Made-With-ML
-
[D] How do you keep up to date on Machine Learning?
Made With ML
- Open-Source Production Machine Learning Course
-
Advice for switching careers within analytics
- Develop a (simple!) ML project and apply MLOps best practices to it. Ask Chat GPT all of your MLOps questions. I've joined this MLOps community and it has been very helpful to know what path to follow in order to be better at MLOps, thanks to them I arrived at madewithml, but I haven't done it yet. But it covers all the MLOps side.
-
Recommendation for MLOps resources
Hey, I’m also working in ML. Here’s a great resource: https://madewithml.com. Also, check out Noah Gift’s book Practical MLOPs.
- Ask HN: Resource to learn how to train and use ML Models
-
Need help to find resources to learn ml ops
Try replicating this setup: https://madewithml.com/
-
MLops Resources
madewithml
-
Ask HN: How do I get started with MLOps?
There's a really nice website by Goku Mohandas called Made With ML. IMO it is the best practical guide to MLOps out there: https://madewithml.com
Incase you want to dive a little deeper, https://fullstackdeeplearning.com/course/2022/ is also something I have been recommended by folks.
- Resources for Current DE Interested in Learning Data Science
-
Do organizations still need machine learning engineers?
madewithml is pretty sweet, especially the MLOps side of things. It'll give you good skills in how development in Python and deploying ML works.
mlops-with-vertex-ai
-
Where to start?
To take it to the next level, maybe start to dive into a truer "end-to-end mlops" example.
- GitHub - GoogleCloudPlatform/mlops-with-vertex-ai: An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI
What are some alternatives?
zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.
mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.
mlops-zoomcamp - Free MLOps course from DataTalks.Club
MLOps - MLOps examples
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
vertex-ai-samples - Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud
nitroml - NitroML is a modular, portable, and scalable model-quality benchmarking framework for Machine Learning and Automated Machine Learning (AutoML) pipelines.
practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book
amazon-sagemaker-examples - Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Copulas - A library to model multivariate data using copulas.
generative-ai - Sample code and notebooks for Generative AI on Google Cloud, including Gemini