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Quantum Machine Learning Presentation Report (PPT)

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Description

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INTRODUCTION

  • Quantum machine learning is the integration of quantum algorithms within machine learning programs.

Quantum Machine Learning Presentation Report

Page Length: 42

Covered Topic :

  • Introduction
  • Linear algebra simulation with quantum amplitudes
  • Quantum Computing
  • Quantum Machine Learning
  • Grover based algorithms for Quantum Machine Learning
  • Grover algorithm
  • Grover algorithm, qRAM version
  • Random Access Memory
  • Quantum Random Access Memory (qRAM)
  • Grover Algorithm and qRAM
  • Type of Complexity Grover Algorithm and qRAM
  • Extended Grover Algorithm and qRAM
  • Machine Learning
  • Nearest-Neighbor Method for Supervised Learning
  • (Unsupervised) Machine Learning
  • Quantum Basic Linear Algebra Subroutines (qBLAS) AKA HHL
  • qBLAS Caveats
  • Quantum tunneling versus thermalization
  • HP’s Dot-Product Engine for Neuromorphic Computing
  • Compute Power, or Data Storage & Movement: Which one is more important in Machine Learning?
  • Adiabatic quantum computation (Quantum Annealing)
  • Optimization, an important ingredient of Machine Learning
  • Conclusion
  • Challenges & Future Work

Additional information

Product Name

Quantum Machine Learning Presentation Report (PPT)

Product Size

3.95 MB

Format

File Format

File Category

DEPARTMENT/COURSE

Need For

College, Semester, University

Product Type

Created By

Abhishek Pal (NIT Agartala)

Uploaded By

Roop Chandra

Requested By

Jaisimha Manipatruni (Nano-Technology Department)

Languages

English

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