sar2160's Stars
alpacahq/alpaca-zipline
Alpaca riding on a zipline
alpacahq/alpaca-backtrader-api
Alpaca Trading API integrated with backtrader
shlomiku/zipline-trader
Zipline Trader, a Pythonic Algorithmic Trading Library with broker integration
ilcardella/TradingBot
Autonomous stocks trading script
uber/orbit
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
alpacahq/pylivetrader
Python live trade execution library with zipline interface.
alpacahq/Momentum-Trading-Example
An example algorithm for a momentum-based day trading strategy.
doccano/doccano
Open source annotation tool for machine learning practitioners.
kelvins/awesome-mlops
:sunglasses: A curated list of awesome MLOps tools
pyro-ppl/numpyro
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
UDST/urbanaccess
A tool for GTFS transit and OSM pedestrian network accessibility analysis by UrbanSim
interpretml/DiCE
Generate Diverse Counterfactual Explanations for any machine learning model.
COVIDExposureIndices/COVIDExposureIndices
Exposure indices derived from PlaceIQ movement data by Couture, Dingel, Green, Handbury, and Williams
gohugoio/hugo
The world’s fastest framework for building websites.
michaelosthege/pyrff
pyrff: Python implementation of random fourier feature approximations for gaussian processes
pysal/mgwr
Multiscale Geographically Weighted Regression (MGWR)
sinhrks/stan-statespace
Stan models for state space time series
andykrause/hpiR
House Price Indexes in R
zillow/battenberg
Providing updates to cookiecutter projects.
uber/manifold
A model-agnostic visual debugging tool for machine learning
trimstray/the-book-of-secret-knowledge
A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.
wsargent/docker-cheat-sheet
Docker Cheat Sheet
MarcSkovMadsen/awesome-streamlit
The purpose of this project is to share knowledge on how awesome Streamlit is and can be
Azure/pixel_level_land_classification
Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
datadesk/census-data-aggregator
Combine U.S. census data responsibly
dask/dask-stories
denadai2/real-estate-neighborhood-prediction
Code to repeat the experiments of "The economic value of neighborhoods: Predicting real estate prices from the urban environment"
hudson-and-thames/mlfinlab
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
chrislgarry/Apollo-11
Original Apollo 11 Guidance Computer (AGC) source code for the command and lunar modules.
ucg8j/awesome-dash
A curated list of awesome Dash (plotly) resources