Comparison of unsupervised machine-learning methods to identify metabolomic signatures in patients with localized breast cancer - ScienceDirect
Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python: Raschka, Sebastian, Liu, Yuxi (Hayden), Mirjalili, Vahid, Dzhulgakov, Dmytro: 9781801819312: Amazon.com: Books
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Accelerating materials property predictions using machine learning | Scientific Reports
Computational sample complexity and attribute-efficient learning | Proceedings of the thirty-first annual ACM symposium on Theory of Computing
Quantum Chemistry in the Age of Machine Learning | The Journal of Physical Chemistry Letters
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Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics | MRS Communications | Cambridge Core
The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks: Roberts, Daniel A., Yaida, Sho, Hanin, Boris: 9781316519332: Amazon.com: Books
Machine learning reduced workload with minimal risk of missing studies: development and evaluation of a randomized controlled trial classifier for Cochrane Reviews - Journal of Clinical Epidemiology
Advancing Biosensors with Machine Learning | ACS Sensors
Computational learning theory | Pattern recognition and machine learning | Cambridge University Press
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Formal Learning Theory (Stanford Encyclopedia of Philosophy)
Computational Learning Theory and Language Acquisition
Frontiers | Applications and Techniques for Fast Machine Learning in Science
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Machine Learning for Transportation | MIT Urban Mobility Lab
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Computation | Free Full-Text | Machine-Learning Methods for Computational Science and Engineering | HTML
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