eo-learn
Made-With-ML
| eo-learn | Made-With-ML | |
|---|---|---|
| 7 | 51 | |
| 1,078 | 35,656 | |
| 0.5% | - | |
| 8.8 | 6.8 | |
| 3 months ago | 5 months ago | |
| Python | Jupyter Notebook | |
| MIT License | MIT License |
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.
eo-learn
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What are examples of well-organized data science project that I can see on Github?
I like ours https://github.com/sentinel-hub/eo-learn but of course I am biased
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Machine Learning free courses online for earth science - suggestions?
Sentinel Hub's eo-learn
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World Mosaic Time-lapse 2020 [3020 × 1510] [OC]
Overall description of used tools: - python: eo-learn and sentinelhub-py - gdal for GIS related stuff - ray for cluster computing
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Transitioning from NLP to satellite and image based CV
If you are joining a not small company they probably already have this, but an example is https://github.com/sentinel-hub/eo-learn which is specific to a certain set of satellite data products.
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Land Cover Classification of Istanbul, Turkey [4965x 2512]
Yes, `eo-learn` is just a collection of the existing tools you mention, which harmonizes the workflow for a specific task. Feel free to open ticket on eo-learn github if you have any questions! :)
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[OC] Vegetation of Africa 2019
* Python packages [sentinelhub-py](https://github.com/sentinel-hub/sentinelhub-py) and [eo-learn](https://github.com/sentinel-hub/eo-learn)
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[OC] Earth in a year (2019 True-Color Sentinel-2 L2A data)
Tools: - Python packages sentinelhub-py and eo-learn - GDAL 3.2
Made-With-ML
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[D] How do you keep up to date on Machine Learning?
Made With ML
- Open-Source Production Machine Learning Course
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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.
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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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Need help to find resources to learn ml ops
Try replicating this setup: https://madewithml.com/
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MLops Resources
madewithml
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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
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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.
What are some alternatives?
gdal - GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.
ml4eo-bootcamp-2021 - Machine Learning for Earth Observation Training of Trainers Bootcamp
mlops-zoomcamp - Free MLOps course from DataTalks.Club
cpython - Alternative StdLib for Nim for Python targets, hijacks Python StdLib for Nim
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
pywsitest - PYthon WebSocket Integration TESTing framework
mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.
eemeter - An open source python package for implementing and developing standard methods for calculating normalized metered energy consumption and avoided energy use.
practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book
styrofoam - (Alpha) Advanced WSGI router for running multiple separate WSGI applications
Copulas - A library to model multivariate data using copulas.