In the decade Because the first Machine Learning course debuted, Python has become the main programming language for AI applications. The assignments and lectures in the new Specialization have been rebuilt to employ Python rather then Octave, like in the first course. 

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Ans. QML is often a technique of mixing machine learning and quantum computing concepts, wherein qubits are applied as an alternative to bits plus the product is trained. QML can help inside the rushing up of present algorithms, the development of new algorithms, and the solution of additional complex algorithms.

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Ans. Quantum machine learning employs the strength of quantum computers to offer faster, additional exact computations and greater scalability.

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Among the most intriguing and potent subfields of machine learning is deep learning, which necessitates in depth matrix and linear multiplication. Substantial matrix multiplication is necessary for neural networks, but loading the same onto a quantum logic gate is usually a non-trivial activity that can be completed very quickly mainly because of the quantum Houses in the gate. This enables the multiplication of an exponentially big matrix with a likewise large vector.

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In the 10 years Because the first Machine Learning course debuted, Python has become the primary programming language for AI applications. The assignments and lectures in the new Specialization are rebuilt to work with Python as opposed to Octave, like in the first course. 

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