lewisbakkero

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"

dataeng-utils

learner-performance-prediction

Simple and performant implementations of learner performance prediction algorithms.

lego_detector

Lego parts classifier using deep neural networks

lewisbakkero/dataeng-utils

lewisbakkero/learner-performance-prediction

Simple and performant implementations of learner performance prediction algorithms.

lewisbakkero/ADS

A list of resources used in Applied Data Science

lewisbakkero/AKT

lewisbakkero/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.

lewisbakkero/causality

lewisbakkero/causalml

Uplift modeling and causal inference with machine learning algorithms

lewisbakkero/cgcnn_bristol

lewisbakkero/childes-db

A SQL interface for the CHILDES child language corpora

lewisbakkero/darts

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

lewisbakkero/das3h

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

lewisbakkero/data-science-interview-assignments

Real data science interview assignments

lewisbakkero/deep-rl-class

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

lewisbakkero/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.

lewisbakkero/dope

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

lewisbakkero/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.

lewisbakkero/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.

lewisbakkero/fastai_dev

development of the next version of fastai

lewisbakkero/GIKT

GIKT: A Graph-based Interaction Model for Knowledge Tracing

lewisbakkero/idealcrap

lewisbakkero/Knowledge-Tracing-SAINT

Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing -Paper Implementation on "Riiid! Answer Correctness Prediction", Kaggle Competition

lewisbakkero/ktm

Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing

lewisbakkero/make-ipinyou-data

This project is to formalise the iPinYou RTB data into a standard format for further researches.

lewisbakkero/MVKM-Multiview-Tensor-EDM2020

lewisbakkero/NeurIPSEducation2020

lewisbakkero/nova-jupyterlab-extensions

lewisbakkero/progress

lewisbakkero/rtb-papers

A collection of research and survey papers of real-time bidding (RTB) based display advertising techniques.

lewisbakkero/SAINT_plus-Knowledge-Tracing-

Implementation of [SAINT+: Integrating Temporal Features for EdNet Correctness Prediction](https://arxiv.org/abs/2010.12042)

lewisbakkero/vaquero