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1. Quantum machine learning

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   Quantum machine learning is an emerging interdisciplinary research area at the intersection of quantum physics and machine learning. The most common use

2. Machine learning

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   for machine learning research Predictive analytics Quantum machine learning Machine-learning applications in bioinformatics Seq2seq Fairness (machine learning)

3. Outline of machine learning

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   Cross-disciplinary fields involving machine learning Adversarial machine learning Predictive analytics Quantum machine learning Robot learning Developmental robotics

4. Machine learning in physics

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   Applying classical methods of machine learning to the study of quantum systems (sometimes called quantum machine learning) is the focus of an emergent

5. List of datasets for machine-learning research

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   for machine-learning research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major

6. Quantum computing

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   Post-quantum cryptography Quantum annealing Quantum bus Quantum cognition Quantum cryptography Quantum logic gate Quantum machine learning Quantum threshold

7. Cambridge Quantum Computing

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   has built enterprise applications for quantum chemistry, quantum machine learning, quantum cryptography and quantum finance. CQC was selected as one of

8. Quantum neural network

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   (which are widely used in machine learning for the important task of pattern classification) with the advantages of quantum information in order to develop

9. Restricted Boltzmann machine

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   classification,collaborative filtering, feature learning,topic modelling and even many body quantum mechanics. They can be trained in either supervised

10. Quantum entanglement

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    Quantum entanglement is the physical phenomenon that occurs when a pair or group of particles is generated, interact, or share spatial proximity in a