hgrif

1on1-questions

Mega list of 1 on 1 meeting questions compiled from a variety to sources

Tutorials

Python data science and machine learning from Ted Petrou with Dunder Data

notears

DAGs with NO TEARS: Continuous Optimization for Structure Learning

causallift

CausalLift: Python package for causality-based Uplift Modeling in real-world business

causalnex

A Python library that helps data scientists to infer causation rather than observing correlation.

stat453-deep-learning-ss20

STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)

pyvtreat

vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distributed under a BSD-3-Clause license.

CausalImpact

An R package for causal inference in time series

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.

gluonts

Probabilistic time series modeling in Python

MarketMatching

causality

In which I play with the ideas surrounding causality

Lyrics-Generation-using-BERT

Generating English Rock lyrics using BERT

jupyter-black

Black formatter for Jupyter Notebook

PandasSchema

A validation library for Pandas data frames using user-friendly schemas

frictionless-py

Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data

sktime

A unified framework for machine learning with time series

convoys

Implementation of statistical models to analyze time lagged conversions

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

mortgages

Compute and compare monthly fees and total burden for mortgages with different periods and interest rates.

MLWatcher

fairlearn

A Python package to assess and improve fairness of machine learning models.

MAPLE

Supervised Local Modeling for Interpretability

platform

Platform for machine learning experiments developed in the project NEWSGAC

deeplearning-models

A collection of various deep learning architectures, models, and tips

pylint-airflow

Pylint plugin for static code analysis on Airflow code

whirl

Fast iterative local development and testing of Apache Airflow workflows

causal_impact

Python package for causal inference using Bayesian structural time-series models.

constrained-classification

Code for H. Narasimhan, "Learning with Complex Loss Functions and Constraints", AISTATS 2018

spektral

Graph Neural Networks with Keras and Tensorflow 2.