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Developer Transition: Machine Learning to Quantum Machine Learning

Offered By: ChemicalQDevice via YouTube

Tags

Quantum Machine Learning Courses Machine Learning Courses TensorFlow Courses Quantum Computing Courses Apache Spark Courses Keras Courses PyTorch Courses scikit-learn Courses Hugging Face Courses

Course Description

Overview

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Explore the transition from classical machine learning to quantum machine learning in this comprehensive webinar presented by ChemicalQDevice CEO Kevin Kawchak. Dive into current machine learning frameworks like PyTorch, TensorFlow, and Keras before delving into quantum computing meetups and resources. Discover quantum machine learning frameworks such as TKET/Quantinuum, Microsoft Q#, AWS Braket, and TorchQuantum. Learn about Pennylane, Qiskit, and Cirq/TensorFlow Quantum implementations. Explore quantum machine learning devices, including NVIDIA GPU Cuquantum Simulators and larger CPU quantum simulators. Gain insights into upcoming developments in quantum machine learning, including dataset processing, qubit physics, and pulse programming. Review key literature from Google and LANL researchers to deepen your understanding of quantum machine learning challenges and opportunities.

Syllabus

Developer Transition: Machine Learning to Quantum Machine Learning


Taught by

ChemicalQDevice

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