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Quantum Computing for AI with Python. Build quantum circuits with Qiskit and explore QML, quantum kernels, QNNs, and hybrid optimization Vivian Aranha

Książka w języku angielskim angielski
Quantum Computing for AI with Python. Build quantum circuits with Qiskit and explore QML, quantum kernels, QNNs, and hybrid optimization Vivian Aranha - okladka książki

Quantum Computing for AI with Python. Build quantum circuits with Qiskit and explore QML, quantum kernels, QNNs, and hybrid optimization Vivian Aranha - okladka książki

Quantum Computing for AI with Python. Build quantum circuits with Qiskit and explore QML, quantum kernels, QNNs, and hybrid optimization Vivian Aranha - audiobook MP3

Quantum Computing for AI with Python. Build quantum circuits with Qiskit and explore QML, quantum kernels, QNNs, and hybrid optimization Vivian Aranha - audiobook CD

Autor:
Vivian Aranha
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
168
Dostępne formaty:
     PDF
     ePub

Ebook
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Do przechowalni

Quantum machine learning sits at the intersection of two fields, yet most learners encounter artificial intelligence and quantum computing as separate subjects. This book bridges that gap with a beginner-friendly, code-led path that explains the classical AI foundations first, then shows how quantum methods are introduced through Python and Qiskit.

You will start with machine learning, model evaluation, neural networks, deep learning, and reinforcement learning using scikit-learn, TensorFlow, and PyTorch. The journey then moves into qubits, superposition, entanglement, measurement, quantum gates, and circuit construction before exploring Grover's search, the Quantum Fourier Transform, phase estimation, and the ideas behind Shor's algorithm.

With these foundations in place, you will explore quantum feature maps, quantum kernels, variational quantum classifiers, quantum neural networks, and hybrid quantum-classical models. The book also introduces QAOA, VQE, quantum annealing, and applied examples in portfolio optimization, quantum chemistry, and cybersecurity. Rather than promising automatic quantum advantage, it helps you understand what these techniques do, how to prototype them, and where they fit alongside classical AI. By the end, you will be able to build and explain practical QML workflows with Python and Qiskit.

O autorze książki

Vivian Aranha is an AI educator, technology leader, and founder of School of AI, with over 20 years of industry experience. He earned a Bachelor's degree in Information Technology in 2004 and a Master's degree in Computer Science in 2006. His career spans web technologies, mobile app development for iOS and Android, blockchain solutions, and AI systems and applications.
Vivian has worked with Fortune 500 organizations, including The Washington Post, Delta Air Lines, and IBM. An instructor since 2009, he has trained professionals worldwide and now teaches AI globally. His courses have attracted over 2.5 million enrollments, with more than 500,000 students learning through School of AI, Udemy, Skool, and Maven.

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