Name: GapData Institute
Type: Organization
Bio: Data. Think. Change. || GapData Institute (GDI) is a nonprofit nonpartisan research institution harnessing power of data & wisdom of economics for public good.
Location: Bratislava, Slovakia
Blog: https://www.gapdata.org/
GapData Institute's Projects
Tutorials for the julia language
Learning Pandas
Learning pandas, Second Edition, published by Packt
Code to get started with a new RStudio project along with data
Notebooks for https://python.quantecon.org
Photos that depict R data structures and operations via Lego
The Less Obvious Conference Checklist
Python library for audio and music analysis
An R package that makes lightgbm models fully interpretable (take reference from https://github.com/AppliedDataSciencePartners/xgboostExplainer)
Local Interpretable Model-Agnostic Explanations (R port of original Python package)
Lime: Explaining the predictions of any machine learning classifier
Simple package for creating LIMEs for XGBoost
Materials for a talk on listening and public speaking
A scripting and command-line front-end for GNU R
Local Interpretable (Model-agnostic) Visual Explanations - model visualization tools for regression problems and tabular data based on LIME method.
A live coding demonstration starting with of a basic example centered around Pandas followed by a more advanced example using topic modeling and subsequent visualization
Prediction of loan defaulter based on more than 5L records using Python, Numpy, Pandas and XGBoost
Understanding complex R objects with tools similar to str()
A repository of journalist's lookup tables.
Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
Includes the source code of the methods which participated in the M4 Competition
The R package M4comp2018 contains the 100000 time series from the M4-competition (https://www.m4.unic.ac.cy/)
:earth_americas: machine learning algorithms tutorials (mainly in Python3)
A complete daily plan for studying to become a machine learning engineer.
Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.
A collection of machine learning examples and tutorials.
Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft
Magenta: Music and Art Generation with Machine Intelligence
Guide to Python's magic methods