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{ "item_title" : "Quantum Machine Learning", "item_author" : [" Siddhartha Bhattacharyya", "Indrajit Pan", "Ashish Mani "], "item_description" : "Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system. While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices. ", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/11/067/064/311067064X_b.jpg", "price_data" : { "retail_price" : "170.99", "online_price" : "170.99", "our_price" : "170.99", "club_price" : "170.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Quantum Machine Learning|Siddhartha Bhattacharyya

Quantum Machine Learning

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Overview

Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system.

While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices.

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Details

  • ISBN-13: 9783110670646
  • ISBN-10: 311067064X
  • Publisher: de Gruyter
  • Publish Date: June 2020
  • Dimensions: 9.9 x 6.9 x 0.6 inches
  • Shipping Weight: 1.05 pounds
  • Page Count: 131

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