jdaubner

jdaubner's Stars

• tidymodels/broom

  Convert statistical analysis objects from R into tidy format

  Language:R1.5k303

• HypothesisWorks/hypothesis

  Hypothesis is a powerful, flexible, and easy to use library for property-based testing.

  Language:Python7.6k588

• jeffkaufman/icdiff

  improved colored diff

  Language:Python4.2k176

• fivethirtyeight/data

  Data and code behind the articles and graphics at FiveThirtyEight

  Language:Jupyter Notebook16.9k10.9k

• PipelineAI/pipeline

  PipelineAI

  Language:Jsonnet4.2k973

• apache/spark

  Apache Spark - A unified analytics engine for large-scale data processing

  Language:Scala40.3k28.4k

• sparklyr/sparklyr

  R interface for Apache Spark

  Language:R957307

• srendle/libfm

  Library for factorization machines

  Language:C++1.5k414

• scalanlp/chalk

  Chalk is a natural language processing library.

  Language:Scala25849

• 8-bit-sheep/googleAnalyticsR

  Use the Google Analytics API from R

  Language:HTML25976

• szilard/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.).

  Language:R1.9k334

• spulec/freezegun

  Let your Python tests travel through time

  Language:Python4.2k271

• mnpk/vim-jira-complete

  AutoComplete JIRA issues in Vim

  Language:VimL8412

• adam-p/markdown-here

  Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.

  Language:JavaScript59.7k11.2k

• lk-geimfari/mimesis

  Mimesis is a robust data generator for Python that can produce a wide range of fake data in multiple languages.

  Language:Python4.5k338

• sfermigier/awesome-functional-python

  A curated list of awesome things related to functional programming in Python.

  2.3k137

• Chicago/food-inspections-evaluation

  This repository contains the code to generate predictions of critical violations at food establishments in Chicago. It also contains the results of an evaluation of the effectiveness of those predictions.

  Language:HTML413131

• geneorama/geneorama

  My main functions

  Language:R52

• ben519/MLPB

  Machine Learning Problem Bible | Problem Set Here >>

  Language:R717275

• ttvand/Santander-Product-Recommendation

  2nd Place Solution of the Kaggle Competition - Santander Product Recommendation

  Language:R173114

• rougier/from-python-to-numpy

  An open-access book on numpy vectorization techniques, Nicolas P. Rougier, 2017

  Language:Python2.1k338

• paucarre/tiefvision

  End-to-end deep learning image-similarity search engine

  Language:Lua764184

• frostming/legit

  Git for Humans, Inspired by GitHub for Mac™.

  Language:Python5.7k217

• kjam/data-pipelines-course

  Course materials for my data pipeline video course with O'Reilly

  Language:Jupyter Notebook194104

• patrickboland4/data_science

  Personal portfolio of data_science: machine learning, visualization, and more

  Language:Jupyter Notebook62

• pixiedust/pixiedust

  Python Helper library for Jupyter Notebooks

  Language:Jupyter Notebook1k161

• kennethreitz/maya

  Datetimes for Humans™

  Language:Python3.4k197

• pep8speaks-org/pep8speaks

  A GitHub :octocat: app to automatically review Python code style over Pull Requests

  Language:Python61386

• lastpass/lastpass-cli

  LastPass command line interface tool

  Language:C2.9k292

• CamDavidsonPilon/lifetimes

  Lifetime value in Python

  Language:Python1.5k375