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Quantum computing is an emerging computational paradigm that uses superposition, entanglement, and interference to solve certain problems more efficiently than classical methods. This paper presents a concise introduction to core quantum concepts and provides practical examples in Python using Qiskit, including a simple factoring illustration, a Bell-state circuit, Grover’s search, and two small supervised-learning examples. The discussion emphasizes both the promise and the current limits of quantum hardware in the NISQ era, with particular attention to applications in optimization, simulation, cryptography, and machine learning. The paper is intended as an accessible starting point for students, researchers, and data scientists who want a hands-on introduction to quantum circuits and algorithms.

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How to choose a machine learning algorithm

Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.

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