mlops-zoomcamp
Made-With-ML
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| mlops-zoomcamp | Made-With-ML | |
|---|---|---|
| 6 | 19 | |
| 3,779 | 30,534 | |
| 8.7% | - | |
| 9.4 | 7.0 | |
| 7 days ago | 10 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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mlops-zoomcamp
- DevOps into MLops crash course
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MLOps zoomcamp
https://particle1331.github.io/inefficient-networks/notebooks/mlops/2-mlflow/2-mlflow.html More info here: https://github.com/DataTalksClub/mlops-zoomcamp
- Is there any advanced data science courses out there?
- Frustrated Data Analyst/Scientist
- mlops-zoomcamp: Free MLOps course from DataTalks.Club
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MLOps Zoomcamp from DataTalks.Club - free course about productionizing ML
Here's more information: https://github.com/DataTalksClub/mlops-zoomcamp
Made-With-ML
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Testing or evaluation libraries
https://madewithml.com covers many practical aspects of machine learning applications.
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What to learn 1-2 months before first MLE job?
There's a lot of good stuff over at https://madewithml.com/ to consider. Their main focus is on MLOps.
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What does learning ML concretely consist of ?
Real world ML does involve a lot, including some of the stuff that falls into MLops (deployment, etc). You can learn a fair amount of that from online resources, such as https://madewithml.com/
- DevOps into MLops crash course
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Where to start?
My favorite"square one" for entrenched DS is https://madewithml.com/, checkout the MLOps section.
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We are re-imagining our ML data stack. What design considerations are most important?
I would recommend taking a look at Made With ML. Good place to start with references on tech.
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From MLE to MLOps
Hey, this will be a goldmine for you: https://madewithml.com It basically has all the aspects and tools of MLOps the way it's done at big tech companies. The explanations are very clear and you'll be able to build an intuition for MLOps. If you have a CS/SWE background, the transition will be smooth. Best of luck!
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[D] Why are there so many blogposts explaining how Conv2D works?
https://madewithml.com/ is a super useful site with a ton of information
- Where to get started with moving from theoretical knowledge to MLOps?
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New to mlops, where do I need to start
Standing recommendation for beginners (we should eventually make a wiki) is https://madewithml.com/
What are some alternatives?
zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.
practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book
FLAML - A fast library for AutoML and tuning.
ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
mlops-course - A project-based course on the foundations of MLOps with a focus on intuition and application.
Copulas - A library to model multivariate data using copulas.
awesome-mlops - A curated list of references for MLOps
stanford-cs229 - 🤖 Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford
SBERT-for-Question-Answering-on-COVID-19-Dataset - Sentence Bert for Question-Answering on COVID-19 Open Research Dataset (CORD-19)
Thin-Plate-Spline-Motion-Model - [CVPR 2022] Thin-Plate Spline Motion Model for Image Animation.
mlattacks - Machine Learning Attack Series
rmi - A learned index structure