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2016-edm

Source code and data sets for Going Deeper with Deep Knowledge Tracing (EDM-2016)

ads

A list of resources used in Applied Data Science

akt

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

bid-lands

bidding-machine

An implementation of the TKDE paper "Bidding Machine: Learning to Bid for Directly Optimizing Profits in Display Advertising"

carinsurance_pricing

This repository illustrates some work in using GLMs to price car insurance based on car insurance policy and claim data. It also features some systematic data exploration and the use of MonteCarlo simulation to investigate the effectiveness of the pricing policies we are using.

categorical

fastai to categorise and predict on tabular data

causality

causalml

Uplift modeling and causal inference with machine learning algorithms

cgcnn_bristol

childes-db

A SQL interface for the CHILDES child language corpora

cytosm

OpenCypher to SQL Mapper

darts

A python library for easy manipulation and forecasting of time series.

das3h

DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills

data-science-interview-assignments

Real data science interview assignments

dataeng-utils

dataviz

Course material for Data Visualization course at Skidmore College

deep-knowledge-tracing-plus

It is the DKT+ model implemented in python3 and tensorflow1.2

deep-rl-class

This repo contain the syllabus of the Hugging Face Deep Reinforcement Learning Class.

deepknowledgetracing

source code for the paper Deep Knowledge Tracing

deeplearning-fastai

Docker image supporting fastai, pytorch, tensorflow, jupyter, and anaconda.

dkt

Our implementation of the LSTM version of Deep Knowledge Tracing (DKT)

dlf

Deep learning for flexible market price modeling (landscape forecasting) in real-time bidding advertising. An implementation of our KDD 2019 paper with some other (Python) implemented prediction models.

dockerfiles

A bunch of docker files to toy around

dope

This reposity holds the code for paper Online Academic Course Performance Prediction using Relational Graph Convolutional Neural Network

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

draggan

Official Code for DragGAN (SIGGRAPH 2023)

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.

fastai_dev

development of the next version of fastai