Made-With-ML
awesome-mlops
Our great sponsors
Made-With-ML | awesome-mlops | |
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51 | 24 | |
35,328 | 11,632 | |
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6.8 | 4.9 | |
4 months ago | 17 days ago | |
Jupyter Notebook | ||
MIT License | - |
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Made-With-ML
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Recommendation for MLOps resources
Hey, Iβm also working in ML. Hereβs a great resource: https://madewithml.com. Also, check out Noah Giftβs book Practical MLOPs.
- Ask HN: Resource to learn how to train and use ML Models
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MLops Resources
madewithml
- Resources for Current DE Interested in Learning Data Science
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Mlops roadmap
Good Reference: https://github.com/visenger/awesome-mlops (The Link above has so many Guides, It's insane) https://madewithml.com/
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How do you build CI/CD pipelines for ML projects?
You can check this site
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[Advice request] How on earth am I supposed to break into machine learning research as an undergraduate?
Great ways to get some experience in general ML: * https://kaggle.com/learn to up your skill-set, practice a bit, and improve breadth of knowledge in topics like deep learning and computer vision * https://huggingface.co/learn free NLP courses that will really beef up your skillset * https://madewithml.com - robust tutorials for the end-to-end deep learning MLOps process * https://roboflow.com/learn - intro course material and some advanced topics in computer vision; tutorial walkthroughs for model training: https://github.com/roboflow/notebooks
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[Q] Any good resources for MLOps?
Made with ML
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Open-source MLOps Fundamentals Course π
Find all the lessons here β https://madewithml.com/MLOps course repo β https://github.com/GokuMohandas/mlops-courseMade With ML repo β https://github.com/GokuMohandas/Made-With-ML
Hi everyone, Iβm the creator of Made With ML and I wanted to share that V1 of the open-source course is finally complete! We cover topics across data β modeling β serving β testing β reproducibility β monitoring β data engineering + more, all with the goal of teaching how to responsibly develop, deploy and maintain production ML applications.* π Project-based* π‘ Intuition (first principles)* π» Implementation (code)* π 30K+ GitHub βοΈ* β€οΈ 40K+ community* β 49 lessons, 100% open-source
awesome-mlops
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Mlops roadmap
Good Reference: https://github.com/visenger/awesome-mlops (The Link above has so many Guides, It's insane) https://madewithml.com/
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Do you wonder why MLOps is not at the same level as DevOps?
I recently did a deep-dive into MLOps for a client, and I've found that https://ml-ops.org/ offers a great overview. Some topics are a bit too "zoomed out", but they still touch on most important aspects of building an end-to-end product. I found it a great starting point when doing research, and picking and choosing some key points from each section + some google helped a lot. Give it a look, you'll probably find some useful things in there.
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MLOps on GitHub Actions with Cirun
MLOps
- DevOps - where to begin?
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JBCNConf 2022: A great farewell
She made mentions to ML-Ops and MLFlow including Vertex AI the GCP implementation. I will post the video as soon as it is available. In the meantime, you can enjoy any other talk from Nerea Luis
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Can Mechanical Engineers become MLOps?
From your post, you seem to be trained for data science for physics modeling, so I'd recommend to get started with https://ml-ops.org/ and for the data engineering part, I found this https://github.com/andkret/Cookbook open source cookbook to be invaluable.
- How to start from scratch?
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Run your first Kubeflow pipeline
Recently I've been learning MLOps. There's a lot to learn, as shown by this and this repository listing MLOps references and tools, respectively.
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Messed up my career by pivoting to DS. Wondering if it's too late to switch to MLE
Awesome MLOps: A collection of MLOps resources.
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MLOps on AWS
ML Ops: Machine Learning Operations
What are some alternatives?
zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book
mlops-zoomcamp - Free MLOps course from DataTalks.Club
mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.
kserve - Standardized Serverless ML Inference Platform on Kubernetes
Copulas - A library to model multivariate data using copulas.
ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
Awesome-Federated-Learning - FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
mlattacks - Machine Learning Attack Series
applied-ml - π Papers & tech blogs by companies sharing their work on data science & machine learning in production.