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Quantum machine learning with microsoft q# at AI Dev Day

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AI has become the most popular buzz word among tech and non-tech individuals and we talk about its applications in daily life. The applications are getting more and more complex, and classical computers are not able to handle most of the work. In this talk, I would like to demonstrate how a hybrid Quantum-Classical Machine Learning model will work and how it can benefit us in the longer run.

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Quantum machine learning with microsoft q# at AI Dev Day

  1. 1. Introduction to Quantum Machine Learning Syed Farhan Founder, QPower Research Microsoft Student Ambassador
  2. 2. DISCUSSION POINTS Overview Introduction to Quantum Systems Qubits & Properties Quantum Entanglement Quantum Entanglement with Q# ML Overview QML Intuition ML vs QML Applications of QML Demo of Classification using Q# Summary
  3. 3. IBM promises 1000-qubit quantum computer—a milestone—by 2023 Source: newsroom.ibm.com QUANTUM IN THE NEWS Quantum Computer with Quantum Volume 64 Source: Honeywell.com 64 Quantum Volume Cloud Accessible Computer Source: newsroom.ibm.com IBM Q System
  4. 4. APPLICATIONS OF QUANTUM COMPUTERS Source: ibm.com
  5. 5. CLASSICAL COMPUTERS
  6. 6. Classical Computing QUBITS IBM Q System Superposition
  7. 7. HADAMARD GATE
  8. 8. MEASUREMENT
  9. 9. QUANTUM ENTANGLEMENT "Spooky Action at a distance" Albert Einstein
  10. 10. Bell Circuit With Microsoft Q#
  11. 11. Approaches to Machine Learning
  12. 12. CC Overview
  13. 13. Hybrid Quantum-Classical: Steps for QML 1. Quantum Embeddings 2. Quantum Variational Circuit 3. Classical Optimizer
  14. 14. Finance Portfolio Analysis in Finance Classification Problems Possibility of classifying very large and complex datasets, such as whether cells are cancerous based on several factors, at a higher speed and lower computation cost. Topological Analysis Hybrid implementations of small-scale quantum computing and powerful classical computing for very large datasets WHERE CAN QML BE USED?
  15. 15. SUMMARY QML is all about uplifting the features of Quantum Computing to do Machine Learning1. It’s not about speedup, but looking at something different entirely 2. We can expect Hybrid Quantum-Classical Architectures in the future 3.
  16. 16. Simple Classifier with Microsoft Q#
  17. 17. THANKS FOR ATTENDING! Follow us on LinkedIn for weekly dose of Quantum Computing: bit.ly/qpowerlinkedin Feel free to reach out for any questions Email: farhan.tuba@gmail.com for comments or questions. You can sign up for Qpower’s Quantum Program here: bit.ly/qpower101

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