Computer science - machine learning

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Accelerating materials science with high-throughput computations and machine learning

Computational Materials Science, 2019
Abstract With unprecedented amounts of materials data generated from experiments as well as high-throughput density functional theory calculations, machine learning techniques has the potential to greatly accelerate materials discovery and design.
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Machine Learning in Building a Collection of Computer Science Course Syllabi

2012
Syllabi are rich educational resources. However, finding Computer Science syllabi on a generic search engine does not work well. Towards our goal of building a syllabus collection we have trained various Decision Tree, Naive-Bayes, Support Vector Machine and Feed-Forward Neural Network classifiers to recognize Computer Science syllabi from other web ...
Nakul Rathod, Lillian N. Cassel
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Using Bayesian Networks and Machine Learning to Predict Computer Science Success

2018
Bayesian Networks and Machine Learning techniques were evaluated and compared for predicting academic performance of Computer Science students at the University of Cape Town. Bayesian Networks performed similarly to other classification models. The causal links inherent in Bayesian Networks allow for understanding of the contributing factors for ...
Zachary Nudelman, Deshendran Moodley, Sonia Berman +2 more
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Machine Learning in Computational Science.

Proposed for presentation at the Artifi cial Intelligence for Earth System Predictability (AI4ESP) in ,, 2021
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Machine learning methods for computational social science

2021
Richard D. De Veaux, Adam Eck
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Computer Science and Machine Learning Trends 2023

2023
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Design of Quantum Machine Learning Course for a Computer Science Program