Quantum Machine Learning: Quantum Algorithms by Pethuru Raj (.ePUB)+
File Size: 34.5 MB
Quantum Machine Learning: Quantum Algorithms and Neural Networks by Pethuru Raj, Houbing Herbert Song, Dac-Nhuong Le, Narayan Vyas
Requirements: .ePUB, .PDF reader, 34.5 MB
Overview: Quantum computing has shown a potential to tackle specific types of problems, especially those involving a daunting number of variables, at an exponentially faster rate compared to classical computers. This volume focuses on quantum variants of Machine Learning algorithms, such as quantum neural networks, quantum reinforcement learning, quantum principal component analysis, quantum support vectors, quantum Boltzmann machines, and many more. Quantum computing (QC) can process calculations tenfold quicker than traditional computing by utilizing the unique characteristics of quantum bits or qubits. The three fundamental ideas of quantum mechanics – superposition, entanglement, and interference – give QC its particular strength. A qubit can store quantum information in a state of superposition, which combines all of the qubit’s potential configurations. Computational spaces can be made complex and multidimensional by using multiple qubits in superposition. These spaces allow for many representations of complex problems.
Genre: Non-Fiction > Tech & Devices
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