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
Pretrained models for Jax/Haiku; MobileNet, ResNet, VGG, Xception.

Pre-trained image classification models for Jax/Haiku Jax/Haiku Applications are deep learning models that are made available alongside pre-trained we

Alper Baris CELIK 14 Dec 20, 2022
small collection of functions for neural networks

neurobiba other languages: RU small collection of functions for neural networks. very easy to use! Installation: pip install neurobiba See examples h

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Build Graph Nets in Tensorflow

Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact DeepMind 5.2k Jan 05, 2023

Distributed Arcface Training in Pytorch

Distributed Arcface Training in Pytorch

3 Nov 23, 2021
Codes for NAACL 2021 Paper "Unsupervised Multi-hop Question Answering by Question Generation"

Unsupervised-Multi-hop-QA This repository contains code and models for the paper: Unsupervised Multi-hop Question Answering by Question Generation (NA

Liangming Pan 70 Nov 27, 2022
Blender Add-on that sets a Material's Base Color to one of Pantone's Colors of the Year

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Don Schnitzius 15 Nov 20, 2022
Implementation of [Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes].

Time2box Implementation of [Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes].

LingCai 4 Aug 23, 2022
The reference baseline of final exam for XMU machine learning course

Mini-NICO Baseline The baseline is a reference method for the final exam of machine learning course. Requirements Installation we use /python3.7 /torc

JoaquinChou 3 Dec 29, 2021
Convert Python 3 code to CUDA code.

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Yuval Rosen 3 Jul 14, 2021
Transfer Learning for Pose Estimation of Illustrated Characters

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Shuhong Chen 142 Dec 28, 2022
A collection of educational notebooks on multi-view geometry and computer vision.

Multiview notebooks This is a collection of educational notebooks on multi-view geometry and computer vision. Subjects covered in these notebooks incl

Max 65 Dec 09, 2022
Pre-trained Deep Learning models and demos (high quality and extremely fast)

OpenVINO™ Toolkit - Open Model Zoo repository This repository includes optimized deep learning models and a set of demos to expedite development of hi

OpenVINO Toolkit 3.4k Dec 31, 2022
Python codes for Lite Audio-Visual Speech Enhancement.

Lite Audio-Visual Speech Enhancement (Interspeech 2020) Introduction This is the PyTorch implementation of Lite Audio-Visual Speech Enhancement (LAVSE

Shang-Yi Chuang 85 Dec 01, 2022
Baseline of DCASE 2020 task 4

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21 Oct 18, 2022
Tensorflow 2 implementation of the paper: Learning and Evaluating Representations for Deep One-class Classification published at ICLR 2021

Deep Representation One-class Classification (DROC). This is not an officially supported Google product. Tensorflow 2 implementation of the paper: Lea

Google Research 137 Dec 23, 2022
Code for "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clouds", CVPR 2021

PV-RAFT This repository contains the PyTorch implementation for paper "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clou

Yi Wei 43 Dec 05, 2022
Direct design of biquad filter cascades with deep learning by sampling random polynomials.

IIRNet Direct design of biquad filter cascades with deep learning by sampling random polynomials. Usage git clone https://github.com/csteinmetz1/IIRNe

Christian J. Steinmetz 55 Nov 02, 2022
Boosted neural network for tabular data

XBNet - Xtremely Boosted Network Boosted neural network for tabular data XBNet is an open source project which is built with PyTorch which tries to co

Tushar Sarkar 175 Jan 04, 2023
Emotional conditioned music generation using transformer-based model.

This is the official repository of EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation. The paper has b

hung anna 96 Nov 09, 2022
Python library for science observations from the James Webb Space Telescope

JWST Calibration Pipeline JWST requires Python 3.7 or above and a C compiler for dependencies. Linux and MacOS platforms are tested and supported. Win

Space Telescope Science Institute 386 Dec 30, 2022