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Software . 2021
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Software . 2021
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Software . 2021
License: http://opensource.org/licenses/MIT
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Software . 2021
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nikosavola/video-game-rating-ml: v1.0.1

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 28 May 2021Publisher:Zenodo
Authors: Savola, Niko;
Code repository: https://github.com/nikosavola/video-game-rating-ml/tree/v1.0.1

doi: 10.5281/zenodo.4876884 , 10.5281/zenodo.4849546 , 10.5281/zenodo.4849545

nikosavola/video-game-rating-ml: v1.0.1

Abstract

Predicting Video Game Rating from Genres using Multilayer Perceptron See live demo on GitHub Pages. Python notebook for training and a .pdf report are included in the training-folder. Originally a project for the course CS-C3240 - Machine Learning provided by Aalto University. Implementation Python & Keras training and model React & TensorFlow.js interactive predictor

Keywords

machine learning, neural network, reactjs, tensorflowjs, video game

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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