JoshFeldman95

JoshFeldman95's Stars

• misaelnieto/vercel-storage

  A wrapper around the vercel storage api

  Language:Python236

• dbt-labs/dbt_metrics

  Macros for calculating metrics

  Language:Python21345

• dbt-labs/dbt-codegen

  Macros that generate dbt code

  Language:Makefile485106

• dbt-labs/dbt-utils

  Utility functions for dbt projects.

  Language:Makefile1.4k496

• httpie/cli

  🥧 HTTPie CLI — modern, user-friendly command-line HTTP client for the API era. JSON support, colors, sessions, downloads, plugins & more.

  Language:Python33.9k3.7k

• Bogdanp/dramatiq

  A fast and reliable background task processing library for Python 3.

  Language:Python4.3k311

• rmcelreath/stat_rethinking_2022

  Statistical Rethinking course winter 2022

  Language:R4.1k445

• erika-e/dotfiles

  Analytics Engineering dotfiles for an M1 Mac

  Language:Shell185

• calogica/dbt-expectations

  Port(ish) of Great Expectations to dbt test macros

  Language:Shell1.1k135

• acmi-lab/cmu-10721-philosophy-machine-intelligence

  Official repository for CMU Machine Learning Department's 10721: "Philosophical Foundations of Machine Intelligence".

  26022

• rguo12/awesome-causality-algorithms

  An index of algorithms for learning causality with data

  2.9k447

• 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 Notebook3.8k716

• huggingface/pytorch-openai-transformer-lm

  🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI

  Language:Python1.5k285

• harvardnlp/namedtensor

  Named Tensor implementation for Torch

  Language:Jupyter Notebook44342

• nitarshan/bayes-by-backprop

  PyTorch implementation of "Weight Uncertainty in Neural Networks"

  Language:Jupyter Notebook17047

• AutoDiffAll/cs207_FinalProject

  Final Project to create a general Auto Differentiation Class

  Language:Python11

• simon555/cs109-FinalProject

  Language:Jupyter Notebook21

• jvanz/pelican-hyde

  Pelican theme based on Hyde Jekyll theme

  Language:CSS12343

• dssg/hitchhikers-guide

  The Hitchhiker's Guide to Data Science for Social Good

  Language:Jupyter Notebook1k282