Raj P. Quantum Machine Learning. Quantum Algorithms and Neural Networks 2024

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Raj P. Quantum Machine Learning. Quantum Algorithms and Neural Networks 2024

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Textbook in PDF format 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. Preface Quantum computing: a paradigm shift from conventional computing An exploration of quantum computing: concept, architecture, and innovative applications Quantum machine learning in healthcare: diagnostics and drug discovery Quantum machine learning in finance Crucial role of blockchain in quantum computing: enhancing security and trust Algorithmic exploration of unveiling fault tolerance in quantum machine learning Quantum machine learning in renewable energy systems Decentralized quantum machine learning: distributed quantum computing for enhanced learning Quantum reinforcement learning: decision-making in quantum environments Quantum machine learning in natural language processing: opportunities and challenges Unveiling intelligence: exploring variational quantum circuits as machine learning models Methods and tools to improve quantum software quality: a survey Quantum-enhanced neural networks: bridging the quantum algorithm and machine learning Future trends and research horizons in quantum machine learning