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Quantum Machine Learning – 01 – Introduction (Summary)

    Quantum Machine learning is the intersection of two concepts, Quantum Mechanics and Machine Learning.

    Quantum Machine Learning = Quantum Mechanics + Classical Machine Learning

    Quantum machine learning uses quantum algorithm instead of classical algorithm.

    Quantum Machine Learning Empowers the classical Machine Learning.

    Quantum Machine Learning uses the Quantum Learning theory

    Quantum learning theory uses the Mathematics of Quantum Generalization.

    Quantum Learning theory is more effective than classical Computer Learner.

    The one of the main goal of Quantum Learning is to reduce the learning time as compare to classical Learning.

    One of the most important Use of Quantum machine Learning is to know the “unknown quantum states”.

    Some of the Companies Uses Quantum machine Learning like D-Wave, Google etc.

    Quantum computers own been making a rapid progress over the last two or three years and they are becoming useful in support of a couple of tasks.

    One of the tasks, we are looking at solving with quantum computers is a couple of challenges in machine learning.

    Quantum computers own been making rapid progress over the last two or three years.

    Source:

    [1] Quantum ML. “Quantum Machine Learning – 01 – Introduction.” YouTube, 27 Dec. 2019, https://www.youtube.com/watch?v=QtWCmO_KIlg&list=PLmRxgFnCIhaMgvot-Xuym_hn69lmzIokg&index=1Accessed 14 Jan. 2021.

    Thumbnail Image Source:

    [1] TheDigitalArtist. “Science Clone Fantasy – Free Image on Pixabay.” Pixabay.com, 9 Mar. 2015, pixabay.com/illustrations/science-clone-fantasy-biology-664427/. Accessed 14 Jan. 2021.

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