eo-learn
mlops-course
| eo-learn | mlops-course | |
|---|---|---|
| 7 | 20 | |
| 1,078 | 2,741 | |
| 0.5% | - | |
| 8.8 | 2.1 | |
| 3 months ago | 9 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
mlops-course
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Ask HN: Daily practices for building AI/ML skills?
coming from a similar context, i believe going top down might be the way to go.
up to your motivation, doing basic level courses first (as shared by others) and then tackling your own application of the concepts might be the way to go.
i also observe the need for strong IT skills for implementing end-to-end ml systems. so, you can play to your strenghts and also consider working on MLOps. (online self-paced course - https://github.com/GokuMohandas/mlops-course)
i went back to school to get structured learning. whether you find it directly useful or not, i found it more effective than just motivating myself to self-learn dry theory. down the line, if you want to go all-in, this might be a good option for you too.
- [Q] Any good resources for MLOps?
- Open-Source Machine Learning for Software Engineers Course
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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
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What are examples of well-organized data science project that I can see on Github?
- https://github.com/GokuMohandas/mlops-course (code for MLOps course)
- Made With ML – develop, deploy and maintain production machine learning
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Where can I learn more about the engineering part of the role?
Haven’t done it but have heard good reviews - https://github.com/GokuMohandas/mlops-course
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Path to ML from a backend engineering role
If MLOps, read https://github.com/GokuMohandas/mlops-course 😎
- What skills should I focus on to improve as a MLE?
- MadeWithML – A practical approach to learning machine learning
What are some alternatives?
gdal - GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
ml4eo-bootcamp-2021 - Machine Learning for Earth Observation Training of Trainers Bootcamp
mlops-with-vertex-ai - An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI
TensorRT - PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
cpython - Alternative StdLib for Nim for Python targets, hijacks Python StdLib for Nim
machine-learning-interview - Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
pywsitest - PYthon WebSocket Integration TESTing framework
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
eemeter - An open source python package for implementing and developing standard methods for calculating normalized metered energy consumption and avoided energy use.
fastai - The fastai deep learning library