rmi
Made-With-ML
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| rmi | Made-With-ML | |
|---|---|---|
| 1 | 51 | |
| 52 | 34,125 | |
| - | - | |
| 0.0 | 5.2 | |
| over 2 years ago | about 1 month ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | MIT License |
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Made-With-ML
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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
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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 🚀
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
Hi everyone, I’m 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 → modeling → serving → testing → reproducibility → monitoring → data engineering + more, all with the goal of teaching how to responsibly develop, deploy and maintain production ML applications.* 🛠 Project-based* 💡 Intuition (first principles)* 💻 Implementation (code)* 🏆 30K+ GitHub ⭐️* ❤️ 40K+ community* ✅ 49 lessons, 100% open-source
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
ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
Copulas - A library to model multivariate data using copulas.
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.
ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
awesome-mlops - A curated list of references for MLOps
Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.
google-research - Google Research
mlattacks - Machine Learning Attack Series