madalsa's Stars
vinta/awesome-python
An opinionated list of awesome Python frameworks, libraries, software and resources.
openai/baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
pyro-ppl/pyro
Deep universal probabilistic programming with Python and PyTorch
rhiever/Data-Analysis-and-Machine-Learning-Projects
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
geopandas/geopandas
Python tools for geographic data
zedr/clean-code-python
:bathtub: Clean Code concepts adapted for Python
shapely/shapely
Manipulation and analysis of geometric objects
justmarkham/scikit-learn-videos
Jupyter notebooks from the scikit-learn video series
gee-community/geemap
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
paulgp/applied-methods-phd
Repo for Yale Applied Empirical Methods PHD Course
openmobilityfoundation/mobility-data-specification
A data standard to enable right-of-way regulation and two-way communication between mobility companies and local governments.
NREL-Sienna/PowerSystems.jl
Data structures in Julia to enable power systems analysis. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.
USEPA/CMAQ
Code for U.S. EPA’s Community Multiscale Air Quality Model (CMAQ) which helps in conducting air quality model simulations
waddell/urban-informatics-and-visualization
Urban Informatics and Visualization (UC Berkeley CP255)
sisl/BayesNets.jl
Bayesian Networks for Julia
thengl/GeoMLA
Machine Learning algorithms for spatial and spatiotemporal data
GeoDS/COVID19USFlows
Multiscale Dynamic Human Mobility Flow Data in the U.S. during the COVID-19 epidemic
CMU-CREATE-Lab/deep-smoke-machine
Deep learning models and dataset for recognizing industrial smoke emissions
PredictiveScienceLab/data-analytics-se
ME 539 - Introduction to Scientific Machine Learning
USEPA/EPA_MOVES_Model
Estimating emissions for mobile sources
niclasmattsson/GlobalEnergyGIS
Generates input data for energy models on renewable energy in arbitrary world regions using public datasets. Written in Julia 1.x.
PacktPublishing/Geospatial-Data-Science-Quick-Start-Guide
Geospatial Data Science Quick Start Guide, published by Packt
MUSA-509/course-materials
Course Materials
transportenergy/database
Tools for accessing and maintaining the iTEM model & historical databases
uky-transport-data-science/ce599
CE599-002 Data Science for Transportation
justinelliotmeyers/INDIA_ATLAS
danielhuppmann/iea-netzero2050-datawrangler
Transform data supporting the IEA Netzero2050 Roadmap (2021) to the IAMC format
epa-kpc/RFMEVAL
marshallblundell/PfE
How Should California Pay for Electricity?Efficiency and Distributional Considerationsof Alternative Funding Mechanisms
ElsevierSoftwareX/SOFTX_2020_107
Data structures in Julia to enable power systems analysis. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021000765