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Work in progress – check back for a more final draft.
A written introduction to convolutional neural networks
This is not meant to be the only outline you read. It’s meant to fill in gaps that others left for me.
A sample problem
Let’s suppose we’re trying to tell sunflowers from tulips in pictures. Suppose every image is grayscale, with 10,000 pixels, with each pixel in the range 0..1.
gdal2 (osgeo/osgeo4mac/gdal2) on macOS 10.12.6 - Homebrew build logs
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This is a discursive recipe for turning the Global Summary of the Day weather dataset into a useful PostgreSQL database on a Unix system. It's aimed at data nerds with no prior knowledge of GSOD. For simplicity, it only describes one way of doing things, but the canny reader will see many possible variations (for example, using staged temporary files rather than a pipeline to do data conversion) and substitutions (mysql for postgres, curl for wget, perl for python, …).
Depending on how you do things, you’ll need something like 50 free gigabytes of disk space to work in, and the final database will use about 20 gigabytes.
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On Oct 7, 2016, at 11:31 AM, No on HH Research Team [email protected] wrote:
If you’re the research team, why are you doing advocacy? What’s the communications team doing right now?
Dear Neighbor,
🤔 Are we neighbors? I would say my neighbors are people close enough that I would walk to visit them. This feels like false intimacy. Why not tell me where you are?
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