Seth Lawler's starred repositories
Simply-Abstract
Discovering how Data Science, Physical Science and How Human Creativity Intersect at Innovation
SimcoeCountyDeploymentGuide
This guide will help you setup the Viewer, API and all its supporting websites.
azure-quickstart-templates
Azure Quickstart Templates
mapboxgl-jupyter
Use Mapbox GL JS to visualize data in a Python Jupyter notebook
GeoStats.jl
An extensible framework for geospatial data science and geostatistical modeling fully written in Julia
geotrellis
GeoTrellis is a geographic data processing engine for high performance applications.
gdal-cheat-sheet
Cheat sheet for GDAL/OGR command-line tools
model-my-watershed
The web application front end for Model My Watershed.
rapid-watershed-delineation
Rapid Watershed Delineation Code for MMW2
jupyter-renderers
Renderers and renderer extensions for JupyterLab
houston_street_flooding
Experimenting with predicting street flooding during the 2017 Subsurface Hackathon in Houston
raster-vision
An open source library and framework for deep learning on satellite and aerial imagery.
own_data_cnn_implementation_keras
A complete tutorial on using own dataset to train a CNN from scratch in Keras (TF & Theano Backend)-
lectures-labs
Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris
hydroshare
HydroShare is a collaborative website for better access to data and models in the hydrologic sciences.
NASA-Training
NASA Remote Sensing for Flood Monitoring and Management
markdown-here
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
benchm-ml
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
asgs
The Automated Solution Generation System (ASGS) provides software infrastructure for automating coastal ocean modelling for real time decision support, and provides a variety of standalone command line tools for pre- and post-processing. Visit us at https://discord.gg/jFbacxrUf9
dataRetrieval
This R package is designed to obtain USGS or EPA water quality sample data, streamflow data, and metadata directly from web services.