Quantum Computing ML

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Quantum Computing is based on quantum mechanics which is solely based on the presence of Quantum Bits or qubits.

Quantum Mechanics postulates suggests that a particle need not exsist in bit 0 or bit 1 state but can also exsist in the superposition of both the bits.

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Basics of Quantum Computing with Machine learning:

1 quantum bit = 2 bits

N quantum Bits = 2^N bits

In classical computer, a classical bit is passed thru a normal logic gate which gives a discrete output , however in the quantum computer, a superpostion bit is passed through the quantum logic gates which in turn gives an entangled superposition bit as the output.

Here in quantum computers, the same input superposition bit can be manipulated to give different output bits using various quantum entanglement in the quantum logic gates.

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Implementation of Quantum Machine Learning

Quantum computing has high processing speed and memory.

It is times faster than ASICs(Application Specific integrated circuits) and FPGAs (Field programmable gate arrays).

Machine Learning topics that can be optimised using Quantum Computing:

Linear Algebra:

Optimization

Kernel evaluation

Deep learning