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Sinopsis
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
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
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.
De la contraportada
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.
You will:
- 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
"Sobre este título" puede pertenecer a otra edición de este libro.
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Edición internacional
Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit
Edición internacionalLibrería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide. Nº de ref. del artículo: ABNR-210138
Cantidad disponible: 2 disponibles
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Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit (Paperback or Softback)
Publicado por
Apress 5/3/2021, 2021
ISBN 10: 1484265211
ISBN 13: 9781484265215
Nuevo
Paperback or Softback
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback or Softback. Condición: New. Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit 1.6. Book. Nº de ref. del artículo: BBS-9781484265215
Cantidad disponible: 5 disponibles
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Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit
Librería: California Books, Miami, FL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: I-9781484265215
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Quantum Machine Learning With Python : Using Cirq from Google Research and IBM Qiskit
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 42575160-n
Cantidad disponible: 4 disponibles
Imagen del vendedor
Quantum Machine Learning with Python
Publicado por
APress, US, 2021
ISBN 10: 1484265211
ISBN 13: 9781484265215
Nuevo
Paperback
Original o primera edición
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. 1st ed. 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 LearnUnderstand Quantum computing and Quantum machine learningExplore varied domains and the scenarios where Quantum machine learning solutions can be appliedDevelop expertise in algorithm development in varied Quantum computing frameworksReview the major challenges of building large scale Quantum computers and applying its various techniquesWho This Book Is ForMachine Learning enthusiasts and engineers who want to quickly scale up to Quantum Machine Learning. Nº de ref. del artículo: LU-9781484265215
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Quantum Machine Learning with Python
Publicado por
APress, US, 2021
ISBN 10: 1484265211
ISBN 13: 9781484265215
Nuevo
Paperback
Original o primera edición
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. 1st ed. 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 LearnUnderstand Quantum computing and Quantum machine learningExplore varied domains and the scenarios where Quantum machine learning solutions can be appliedDevelop expertise in algorithm development in varied Quantum computing frameworksReview the major challenges of building large scale Quantum computers and applying its various techniquesWho This Book Is ForMachine Learning enthusiasts and engineers who want to quickly scale up to Quantum Machine Learning. Nº de ref. del artículo: LU-9781484265215
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Quantum Machine Learning With Python : Using Cirq from Google Research and IBM Qiskit
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 42575160
Cantidad disponible: 4 disponibles
Imagen del vendedor
Quantum Machine Learning with Python
Publicado por
APress, US, 2021
ISBN 10: 1484265211
ISBN 13: 9781484265215
Nuevo
Paperback
Original o primera edición
Librería: Rarewaves.com UK, London, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. 1st ed. 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 LearnUnderstand Quantum computing and Quantum machine learningExplore varied domains and the scenarios where Quantum machine learning solutions can be appliedDevelop expertise in algorithm development in varied Quantum computing frameworksReview the major challenges of building large scale Quantum computers and applying its various techniquesWho This Book Is ForMachine Learning enthusiasts and engineers who want to quickly scale up to Quantum Machine Learning. Nº de ref. del artículo: LU-9781484265215
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. In. Nº de ref. del artículo: ria9781484265215_new
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Quantum Machine Learning with Python
Publicado por
APress, US, 2021
ISBN 10: 1484265211
ISBN 13: 9781484265215
Nuevo
Paperback
Original o primera edición
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. 1st ed. 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 LearnUnderstand Quantum computing and Quantum machine learningExplore varied domains and the scenarios where Quantum machine learning solutions can be appliedDevelop expertise in algorithm development in varied Quantum computing frameworksReview the major challenges of building large scale Quantum computers and applying its various techniquesWho This Book Is ForMachine Learning enthusiasts and engineers who want to quickly scale up to Quantum Machine Learning. Nº de ref. del artículo: LU-9781484265215
Cantidad disponible: Más de 20 disponibles