Philip Chmielowiec (philipc2)

philipc2

Geek Repo

Company:@NCAR

Location:Chicago, IL

Home Page:philipc@ucar.edu

Github PK Tool:Github PK Tool


Organizations
Climate-Dynamics-and-Data-Science-Group
NCAR
UXARRAY

Philip Chmielowiec's repositories

sci-sonify

Turn Scientific Data into Sounds & Music

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siparcs-project-13

Project Management for Project 13

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advanced-viz-cookbook

A cookbook to demonstrate advanced visualization techniques using matplotlib, cartopy, metpy, and geocat-viz.

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airport-assistant

Airport Assistant using the OpenFlights dataset

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carla

Open-source simulator for autonomous driving research.

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CDDS-Python

A collection of Python code and notebooks related to Climate Science

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cheyenne-cesm2

Collection of documentation, tutorials, and notebooks highlighting how to set up, run, and analyze CESM2 simulations on the Cheyenne Supercomputer

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emergency-vehicle-detection

Emergency Vehicle Detection implemented on the AutonomouStuff GEM e2 autonomous vehicle

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ncsa-ashby-hackathon

Deep learning climate aerosol model trained on general circulation model (GCM) features

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SSF-Transfer-Learning

Extension of the SSF codebase to support the CESM2 Forecast and Reforecast dataset and Transfer Learning

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accelerated-computing-hub

NVIDIA curated collection of educational resources related to general purpose GPU programming.

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antimeridian

Fix GeoJSON polygons that cross the antimeridian

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cdds-at-uiuc.github.io

CDDS@UIUC Group Website!

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cv-quad-day-showcase

Interactive Computer Vision Showcase for Quad Day 2022

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philipc2

Config files for my GitHub profile.

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spatialpandas

Pandas extension arrays for spatial/geometric operations

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ugrid-conventions

Unstructured Grid (UGRID) Conventions

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uxarray

Xarray-styled package for reading and directly operating on unstructured grid datasets following UGRID conventions

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uxarray-feedstock

A conda-smithy repository for uxarray.

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vast

Hugo content for the VAST GitHub Pages site

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web-map-feature-services-cookbook

Web map/feature services can help provide the necessary spatial context to your data.

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