eo-learn
Earth observation processing framework for machine learning in Python (by sentinel-hub)
Kedro
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular. (by kedro-org)
| eo-learn | Kedro | |
|---|---|---|
| 7 | 29 | |
| 1,078 | 9,398 | |
| 0.5% | 1.1% | |
| 8.1 | 9.7 | |
| 9 days ago | 5 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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
Posts with mentions or reviews of eo-learn.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-05.
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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
Kedro
Posts with mentions or reviews of Kedro.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-10.
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Nextflow: Data-Driven Computational Pipelines
Interesting, thanks for sharing. I'll definitely take a look, although at this point I am so comfortable with Snakemake, it is a bit hard to imagine what would convince me to move to another tool. But I like the idea of composable pipelines: I am building a tool (too early to share) that would allow to lay Snakemake pipelines on top of each other using semi-automatic data annotations similar to how it is done in kedro (https://github.com/kedro-org/kedro).
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A Polars exploration into Kedro
# pyproject.toml [project] dependencies = [ "kedro @ git+https://github.com/kedro-org/kedro@3ea7231", "kedro-datasets[pandas.CSVDataSet,polars.CSVDataSet] @ git+https://github.com/kedro-org/kedro-plugins@3b42fae#subdirectory=kedro-datasets", ]
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What are some open-source ML pipeline managers that are easy to use?
So there's 2 sides to pipeline management: the actual definition of the pipelines (in code) and how/when/where you run them. Some tools like prefect or airflow do both of them at once, but for the actual pipeline definition I'm a fan of https://kedro.org. You can then use most available orchestrators to run those pipelines on whatever schedule and architecture you want.
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How do data scientists combine Kedro and Databricks?
We have set up a milestone on GitHub so you can check in on our progress and contribute if you want to. To suggest features to us, report bugs, or just see what we're working on right now, visit the Kedro projects on GitHub.
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How do you organize yourself during projects?
you could use a project framework like kedro to force you to be more disciplined about how you structure your projects. I'd also recommend checking out this book: Edna Ridge - Guerrilla Analytics: A Practical Approach to Working with Data
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Futuristic documentation systems in Python, part 1: aiming for more
Recently I started a position as Developer Advocate for Kedro, an opinionated data science framework, and one of the things we're doing is exploring what are the best open source tools we can use to create our documentation.
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Python projects with best practices on Github?
You can also check out Kedro, it’s like the Flask for data science projects and helps apply clean code principles to data science code.
- Data Science/ Analyst Zertifikate für den Job Markt?
- What are examples of well-organized data science project that I can see on Github?
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Dabbling with Dagster vs. Airflow
An often overlooked framework used by NASA among others is Kedro https://github.com/kedro-org/kedro. Kedro is probably the simplest set of abstractions for building pipelines but it doesn't attempt to kill Airflow. It even has an Airflow plugin that allows it to be used as a DSL for building Airflow pipelines or plug into whichever production orchestration system is needed.
What are some alternatives?
When comparing eo-learn and Kedro you can also consider the following projects:
gdal - GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
ml4eo-bootcamp-2021 - Machine Learning for Earth Observation Training of Trainers Bootcamp
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
Dask - Parallel computing with task scheduling
cpython - Alternative StdLib for Nim for Python targets, hijacks Python StdLib for Nim
cookiecutter-pytorch - A Cookiecutter template for PyTorch Deep Learning projects.
pywsitest - PYthon WebSocket Integration TESTing framework
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
eemeter - An open source python package for implementing and developing standard methods for calculating normalized metered energy consumption and avoided energy use.
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!