Platforms, Tools and Packages for Geospatial/Earth Observation Data Scientists. In this article, I highlight the best open source tools in the market that are integrated into the data science ecosystem.
The satellite-based earth observation data is increasing at a rapid base, thanks to technological development in remote sensing platforms, and breakthroughs in data collection and storage. Today, we have more than 768 earth observation satellites in orbit, compared with only 150 in 2018.
As a Geospatial or earth observation data scientist, you have a vast array of tools and resources to choose. In this article, I highlight the best open source tools in the market that are integrated into the data science ecosystem.
Your wish granted. GEE is all in one package. Google Earth Engine(GEE) is by far the complete one in all package for earth observation data scientists. It does offer not only Geospatial data processing and analysis capabilities but also provides ready to use datasets to focus on analysing rather than downloading data.
With GEE, you can perform planetary-scale analysis with freely available satellite images from NASA/USGS (Landsat, MODIS), European Union (Sentinel 1 & 2) and non-satellite or derived products like elevation, climate data and land cover.
Furthermore, you can create Machine Learning models right with GEE and can produce full ML models and predictions right in the browser. The python module integrates well with other python packages, and you can run in Jupyter notebooks or Google Colab.
There you go — a complete end-to-end functionality in GEE with terabytes of satellite imagery sources, data processing tools and ML algorithms, right in your browser.
It could not have been better!
Learning is a new fun in the field of Machine Learning and Data Science. In this article, we’ll be discussing 15 machine learning and data science projects.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
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In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics.
This post will help you in finding different websites where you can easily get free Datasets to practice and develop projects in Data Science and Machine Learning.