Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit

Pattanayak, Santanu

  • 出版商: Apress
  • 出版日期: 2021-03-13
  • 售價: $1,600
  • 貴賓價: 9.5$1,520
  • 語言: 英文
  • 頁數: 359
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484265211
  • ISBN-13: 9781484265215
  • 相關分類: Python程式語言Machine Learning量子 Quantum
  • 立即出貨 (庫存=1)

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商品描述

Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particles. It also examines Quantum machine learning, which can help solve some of the most challenging problems in forecasting, financial modeling, genomics, cybersecurity, supply chain logistics, cryptography among others.
You'll start by reviewing the fundamental concepts of Quantum Computing, such as Dirac Notations, Qubits, and Bell state, followed by postulates and mathematical foundations of Quantum Computing. Once the foundation base is set, you'll delve deep into Quantum based algorithms including Quantum Fourier transform, phase estimation, and HHL (Harrow-Hassidim-Lloyd) among others.
You'll then be introduced to Quantum machine learning and Quantum deep learning-based algorithms, along with advanced topics of Quantum adiabatic processes and Quantum based optimization. Throughout the book, there are Python implementations of different Quantum machine learning and Quantum computing algorithms using the Qiskit toolkit from IBM and Cirq from Google Research.
What You'll Learn

  • Understand Quantum computing and Quantum machine learning
  • Explore varied domains and the scenarios where Quantum machine learning solutions can be applied
  • Develop expertise in algorithm development in varied Quantum computing frameworks
  • Review the major challenges of building large scale Quantum computers and applying its various techniques

Who This Book Is For
Machine Learning enthusiasts and engineers who want to quickly scale up to Quantum Machine Learning

 

商品描述(中文翻譯)

快速擴展至量子計算和量子機器學習基礎以及相關數學,並將其應用於可以通過基於量子的算法解決的不同用例。本書解釋了利用量子力學性質的量子計算。它還探討了可以幫助解決預測、金融建模、基因組學、網絡安全、供應鏈物流、加密等一些最具挑戰性問題的量子機器學習。

您將首先回顧量子計算的基本概念,如狄拉克符號、量子位和貝爾狀態,然後是量子計算的公理和數學基礎。一旦建立了基礎,您將深入研究基於量子的算法,包括量子傅立葉變換、相位估計和HHL(Harrow-Hassidim-Lloyd)等。

然後,您將介紹量子機器學習和基於量子的深度學習算法,以及量子絕熱過程和基於量子的優化的高級主題。在整本書中,使用IBM的Qiskit工具包和Google Research的Cirq,實現了不同的量子機器學習和量子計算算法的Python實現。

您將學到什麼
- 理解量子計算和量子機器學習
- 探索不同領域以及可以應用量子機器學習解決方案的情景
- 在不同的量子計算框架中開發算法開發專業知識
- 檢視構建大規模量子計算機和應用其各種技術的主要挑戰

本書適合對象
- 機器學習愛好者和工程師,希望快速擴展至量子機器學習

作者簡介

Santanu Pattanayak works as a staff machine learning specialist at Qualcomm Corp R&D and is an author of the book "Pro Deep Learning with TensorFlow" published by Apress. He has around 12 years of work experience and has worked at GE, Capgemini, and IBM before joining Qualcomm. He graduated with a degree in electrical engineering from Jadavpur University, Kolkata and is an avid math enthusiast. Santanu has a master's degree in data science from Indian Institute of Technology (IIT), Hyderabad. He also participates in Kaggle competitions in his spare time where he ranks in top 500. Currently, he resides in Bangalore with his wife.

作者簡介(中文翻譯)

Santanu Pattanayak 在高通公司研發部門擔任機器學習專家,並且是由Apress出版的書籍「Pro Deep Learning with TensorFlow」的作者。他擁有約12年的工作經驗,在加入高通之前曾在GE、Capgemini和IBM工作。他畢業於加爾各答的Jadavpur大學,獲得電機工程學位,同時也是一位熱衷於數學的愛好者。Santanu在印度理工學院(IIT)海得拉巴校區獲得了數據科學碩士學位。他在空閒時間也參加Kaggle競賽,並在其中排名前500名。目前,他與妻子居住在班加羅爾。