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Build machine learning models in Python using well known machine learning libraries NumPy & scikit-learn
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Hardware restrictions: In an effort to be employed for machine learning applications in the true world, quantum computers nevertheless Possess a great distance to go resulting from major hardware constraints.
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The most intriguing and powerful subfields of machine learning is deep learning, which necessitates in depth matrix and linear multiplication. Substantial matrix multiplication is needed for neural networks, but loading the same onto a quantum logic gate is often a non-trivial task that may be completed in a short time as a result of quantum Homes in the gate. This permits the multiplication of the exponentially massive matrix with a likewise massive vector.
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In quantum algorithms with AI the decade Because the first Machine Learning course debuted, Python has become the main programming language for AI applications. The assignments and check here lectures in the new Specialization are actually rebuilt to make use of Python as opposed to Octave, like in the original course.
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• Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn.