A curated list of awesome game datasets, and tools to artificial intelligence in games

Overview

🎮 Awesome Game Datasets Awesome

In computer science, Artificial Intelligence (AI) is intelligence demonstrated by machines. Its definition, AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that achieving its goals Russell et. al (2016).

Withal, Data Mining (DM) is the process of discovering patterns in data sets (or datasets) involving methods of machine learning, statistics, and database systems; DM focus on extract the information of datasets Han (2011).

This repository serves as a guide for anyone who wants to work with Artificial Intelligence or Data Mining applied in digital games! Here you will find a series of datasets, tools and materials available to build your application or dataset.

Contributing

Any suggestions or doubts, please open an "issue". If you want to contribute, read this and make a "pull request".


Contents


API

API is "a set of functions and procedures allowing the creation of applications that access the features or data of an operating system, application, or other service" (Google).


Artificial Intelligence

Mobile

Web


Books

  • Drachen, A. Mirza-Babaei, P. Nacke, L. (2018). Games user research. Oxford.
  • El-Nasr, S. Drachen, A. Canossa, A. (2013). Game analytics: maximizing the value of player data. Sprigner.
  • Han, J., Pei, J., Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.
  • Hennig-Thurau, T. Houston, M. (2018). Entertainment science: data analytics and practical theory for movies, games, music and books. Springer.
  • Loh, A. Sheng, Y. Ifenthaler, D. (2015). Serious games analytics: methodologies for performance measurement, assessment, and improvement. Springer.
  • Russell, S. J., Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited.
  • Yannakakis, G. N., Togelius, J. (2018). Artificial intelligence and games. Springer.

Dataset

Related


Market Research


Miscellaneous


License

Creative Commons License

Owner
Leonardo Mauro
Data Scientist | Professor (Data Mining, Machine Learning, Business Intelligence).
Leonardo Mauro
Data Augmentation with Variational Autoencoders

Documentation Pyraug This library provides a way to perform Data Augmentation using Variational Autoencoders in a reliable way even in challenging con

112 Nov 30, 2022
Rule-based Customer Segmentation

Rule-based Customer Segmentation Business Problem A game company wants to create level-based new customer definitions (personas) by using some feature

Cem Çaluk 2 Jan 03, 2022
Implementation of 'X-Linear Attention Networks for Image Captioning' [CVPR 2020]

Introduction This repository is for X-Linear Attention Networks for Image Captioning (CVPR 2020). The original paper can be found here. Please cite wi

JDAI-CV 240 Dec 17, 2022
Deep deconfounded recommender (Deep-Deconf) for paper "Deep causal reasoning for recommendations"

Deep Causal Reasoning for Recommender Systems The codes are associated with the following paper: Deep Causal Reasoning for Recommendations, Yaochen Zh

Yaochen Zhu 22 Oct 15, 2022
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)

Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CAC) Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Li

DV Lab 137 Dec 14, 2022
Brain Tumor Detection with Tensorflow Neural Networks.

Brain-Tumor-Detection A convolutional neural network model built with Tensorflow & Keras to detect brain tumor and its different variants. Data of the

404ErrorNotFound 5 Aug 23, 2022
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking

Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking We revisit and address issues with Oxford 5k and Paris 6k image retrieval benchm

Filip Radenovic 188 Dec 17, 2022
Image Fusion Transformer

Image-Fusion-Transformer Platform Python 3.7 Pytorch =1.0 Training Dataset MS-COCO 2014 (T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ram

Vibashan VS 68 Dec 23, 2022
Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps

Proximal Backpropagation Proximal Backpropagation (ProxProp) is a neural network training algorithm that takes implicit instead of explicit gradient s

Thomas Frerix 40 Dec 17, 2022
Parallel Latent Tree-Induction for Faster Sequence Encoding

FastTrees This repository contains the experimental code supporting the FastTrees paper by Bill Pung. Software Requirements Python 3.6, NLTK and PyTor

Bill Pung 4 Mar 29, 2022
Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination

Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination Pratul P. Srinivasan, Ben Mildenhall, Matthew Tancik, Jonathan T. Barron,

Pratul Srinivasan 65 Dec 14, 2022
Rohit Ingole 2 Mar 24, 2022
Denoising Diffusion Probabilistic Models

Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay Jain, Pieter Abbeel Paper: https://arxiv.org/abs/2006.11239 Website: https://hojonathanho.g

Jonathan Ho 1.5k Jan 08, 2023
UT-Sarulab MOS prediction system using SSL models

UTMOS: UTokyo-SaruLab MOS Prediction System Official implementation of "UTMOS: UTokyo-SaruLab System for VoiceMOS Challenge 2022" submitted to INTERSP

sarulab-speech 58 Nov 22, 2022
Official Code Release for Container : Context Aggregation Network

Container: Context Aggregation Network Official Code Release for Container : Context Aggregation Network Comparion between CNN, MLP-Mixer and Transfor

peng gao 42 Nov 17, 2021
A Domain-Agnostic Benchmark for Self-Supervised Learning

DABS: A Domain Agnostic Benchmark for Self-Supervised Learning This repository contains the code for DABS, a benchmark for domain-agnostic self-superv

Alex Tamkin 81 Dec 09, 2022
An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches

Transformer-in-Transformer An Implementation of the Transformer in Transformer paper by Han et al. for image classification, attention inside local pa

Rishit Dagli 40 Jul 25, 2022
Adds timm pretrained backbone to pytorch's FasterRcnn model

Operating Systems Lab (ETCS-352) Experiments for Operating Systems Lab (ETCS-352) performed by me in 2021 at uni. All codes are written by me except t

Mriganka Nath 12 Dec 03, 2022
🏎️ Accelerate training and inference of 🤗 Transformers with easy to use hardware optimization tools

Hugging Face Optimum 🤗 Optimum is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to t

Hugging Face 842 Dec 30, 2022
An open-source, low-cost, image-based weed detection device for fallow scenarios.

Welcome to the OpenWeedLocator (OWL) project, an opensource hardware and software green-on-brown weed detector that uses entirely off-the-shelf compon

Guy Coleman 145 Jan 05, 2023