Quantum Machine Learning With Python

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  • Author : Santanu Pattanayak
  • Publisher : Apress
  • Pages : 295 pages
  • ISBN : 9781484265215
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Quantum Machine Learning With Python

Download or Read online Quantum Machine Learning With Python full in PDF, ePub and kindle. this book written by Santanu Pattanayak and published by Apress which was released on 29 March 2021 with total page 295 pages. We cannot guarantee that Quantum Machine Learning With Python book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Quantum Machine Learning With Python

Quantum Machine Learning With Python
  • Author : Santanu Pattanayak
  • Publisher : Apress
  • Release : 29 March 2021
GET THIS BOOK Quantum Machine Learning With Python

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,

Quantum Machine Learning

Quantum Machine Learning
  • Author : Siddhartha Bhattacharyya,Indrajit Pan,Ashish Mani,Sourav De,Elizabeth Behrman,Susanta Chakraborti
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 08 June 2020
GET THIS BOOK Quantum Machine Learning

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

Quantum Machine Learning

Quantum Machine Learning
  • Author : Peter Wittek
  • Publisher : Academic Press
  • Release : 10 September 2014
GET THIS BOOK Quantum Machine Learning

Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary

Supervised Learning with Quantum Computers

Supervised Learning with Quantum Computers
  • Author : Maria Schuld,Francesco Petruccione
  • Publisher : Springer
  • Release : 30 August 2018
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Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses

Machine Learning with Quantum Computers

Machine Learning with Quantum Computers
  • Author : Maria Schuld,Francesco Petruccione
  • Publisher : Springer Nature
  • Release : 18 November 2021
GET THIS BOOK Machine Learning with Quantum Computers

This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate

Quantum Machine Learning An Applied Approach

Quantum Machine Learning  An Applied Approach
  • Author : Santanu Ganguly
  • Publisher : Apress
  • Release : 11 August 2021
GET THIS BOOK Quantum Machine Learning An Applied Approach

Know how to adapt quantum computing and machine learning algorithms. This book takes you on a journey into hands-on quantum machine learning (QML) through various options available in industry and research. The first three chapters offer insights into the combination of the science of quantum mechanics and the techniques of machine learning, where concepts of classical information technology meet the power of physics. Subsequent chapters follow a systematic deep dive into various quantum machine learning algorithms, quantum optimization, applications of

Hands On Quantum Machine Learning With Python

Hands On Quantum Machine Learning With Python
  • Author : Frank Zickert
  • Publisher : Independently Published
  • Release : 19 June 2021
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You're interested in quantum computing and machine learning. But you don't know how to get started? Let me help! Whether you just get started with quantum computing and machine learning or you're already a senior machine learning engineer, Hands-On Quantum Machine Learning With Python is your comprehensive guide to get started with Quantum Machine Learning - the use of quantum computing for the computation of machine learning algorithms. Quantum computing promises to solve problems intractable with current computing technologies. But

Principles Of Quantum Artificial Intelligence Quantum Problem Solving And Machine Learning Second Edition

Principles Of Quantum Artificial Intelligence  Quantum Problem Solving And Machine Learning  Second Edition
  • Author : Andreas Miroslaus Wichert
  • Publisher : World Scientific
  • Release : 08 July 2020
GET THIS BOOK Principles Of Quantum Artificial Intelligence Quantum Problem Solving And Machine Learning Second Edition

This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds.

Quantum Computing with Silq Programming

Quantum Computing with Silq Programming
  • Author : Srinjoy Ganguly,Thomas Cambier
  • Publisher : Packt Publishing Ltd
  • Release : 30 April 2021
GET THIS BOOK Quantum Computing with Silq Programming

Silq is a new high-level programming language to program quantum computers easily. Silq is set to revolutionize quantum programming just as the C programming language did for classical computers. Quantum Computing with Silq will prepare you for the quantum revolution and enable you to start building software and application programs for ...

Supervised Learning with Quantum Computers

Supervised Learning with Quantum Computers
  • Author : Maria Schuld,Francesco Petruccione
  • Publisher : Springer
  • Release : 12 October 2018
GET THIS BOOK Supervised Learning with Quantum Computers

This book investigates how quantum computers can be used for data-driven prediction. It summarizes and conceptualizes ideas that have been proposed in the discipline of quantum machine learning to provide a starting point for those new to the field, while serving as a reference for readers familiar with the topic. Given the interdisciplinary nature of the subject, the first chapters work through a simple but illustrative quantum machine learning algorithm and give a detailed overview of the parent disciplines. The

Quantum Computing Physics Blockchains And Deep Learning Smart Networks

Quantum Computing  Physics  Blockchains  And Deep Learning Smart Networks
  • Author : Melanie Swan,Renato P Dos Santos,Frank Witte
  • Publisher : World Scientific
  • Release : 20 March 2020
GET THIS BOOK Quantum Computing Physics Blockchains And Deep Learning Smart Networks

Quantum information and contemporary smart network domains are so large and complex as to be beyond the reach of current research approaches. Hence, new theories are needed for their understanding and control. Physics is implicated as smart networks are physical systems comprised of particle-many items interacting and reaching criticality and emergence across volumes of macroscopic and microscopic states. Methods are integrated from statistical physics, information theory, and computer science. Statistical neural field theory and the AdS/CFT correspondence are employed