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Quantum Machine Learning | 2021 Qiskit Global Summer School

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Lecture 7.1 - Quantum Kernels in Practice

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Lecture 6.2 - Quantum Feature Spaces and Kernels

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Lecture 6.1 - From Variational Classifiers to Linear Classifiers

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Lecture 5.2 - Introduction to the Quantum Approximate Optimization Algorithm and Applications

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Lecture 5.1 - Building a Quantum Classifier

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Lecture 4.2 - Advanced Classical Machine Learning (ML)

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Lecture 4.1 - Introduction to Classical Machine Learning (ML)

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Lecture 3.2 - Noise in Quantum Computers - part 2

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Lecture 3.1 - Noise in Quantum Computers - part 1

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Lecture 2.2 - Simple Quantum Algorithms II

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Lecture 2.1 - Simple Quantum Algorithms I

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Lecture 1.2 - Introduction to Quantum Circuits

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Lab 2 - Introduction to Variational Algorithms

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Lecture 1.1 - Vector Spaces, Tensor Products, and Qubits

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Lab 1 - Introduction to Quantum Computing Algorithms and Operations

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