adisetyop

adisetyop's Stars

• jrfiedler/causal_inference_python_code

  Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

  Language:Jupyter Notebook1.3k389

• DaveStrickland/AstroPhotography

  Python workflow for processing astrophotography images from either digital cameras and/or amateur telescopes.

  Language:Jupyter Notebook224

• dancoe/Trilogy

  Trilogy color images

  Language:Jupyter Notebook10

• devzhk/LMCTS

  Language:Python105

• zoj613/polyagamma

  An efficient and flexible sampler of the Pólya-Gamma distribution with a NumPy/SciPy compatible interface.

  Language:C244

• DavisTrey/ExperimentationResources

  A list of blogs, videos, and other content that provides advice on building experimentation and A/B testing platforms

  15121

• GoogleCloudPlatform/ml-design-patterns

  Source code accompanying O'Reilly book: Machine Learning Design Patterns

  Language:Jupyter Notebook1.9k533

• py-why/EconML

  ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

  Language:Jupyter Notebook3.9k725

• avehtari/BDA_course_Aalto

  Bayesian Data Analysis course at Aalto

  Language:TeX2.2k558

• guillermo-navas-palencia/cprior

  Fast Bayesian A/B and Multivariate testing.

  Language:Python366

• pyro-ppl/numpyro

  Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

  Language:Python2.4k246

• arviz-devs/arviz

  Exploratory analysis of Bayesian models with Python

  Language:Python1.6k410

• nalepae/pandarallel

  A simple and efficient tool to parallelize Pandas operations on all available CPUs

  Language:Python3.7k215

• aloctavodia/Statistical-Rethinking-with-Python-and-PyMC3

  Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath

  Language:Jupyter Notebook840255

• danieledurante/ProbitSUN

  Conjugate Bayes for probit regression via unified skew-normal distributions

  42

• ImperialCollegeLondon/covid19model

  Code for modelling estimated deaths and cases for COVID19.

  Language:Stan945272

• damitkwr/ESRNN-GPU

  PyTorch GPU implementation of the ES-RNN model for time series forecasting

  Language:Python31972