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Item #:
86456855
A Practical Guide to Quantum Machine Learning and Quantum Optimization: Hands-on Approach to Modern Quantum Algorithms
86% of respondents would recommend this to a friend
Item #:
86456855
DKK 507
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What Stands Out
Hands-on Learning
This guide utilizes a practical approach, allowing readers to actively engage with quantum algorithms, ensuring a deeper understanding of concepts compared to purely theoretical resources.
Modern Algorithms Focus
The book covers contemporary quantum algorithms, addressing current challenges in quantum machine learning and optimization, which positions it as highly relevant for today's rapidly evolving tech landscape.
Expert Insights
Authored by experts in the field, this guide provides valuable insights and real-world applications, enhancing learning and confidence for both beginners and experienced practitioners in quantum computing.
Product Details
| Publisher | Packt Publishing |
| Publication date | March 31, 2023 |
| Edition | 1st |
| Language | English |
| Print length | 680 pages |
| ISBN-10 | 1804613835 |
| ISBN-13 | 978-1804613832 |
| Item Weight | 2.53 pounds (1.15 kg) |
| Dimensions | 7.5 x 1.6 x 9.25 inches (19.1 x 4.1 x 23.5 cm) |
Who Should Buy?
-
Quantum Enthusiasts
Individuals eager to explore and understand quantum computing applications in machine learning and optimization techniques.
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Data Scientists
Practitioners wanting to enhance their skill set with modern quantum algorithms applicable in data analysis and modeling.
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Graduate Students
Students in computational fields looking for practical guidance on applying quantum algorithms to their research projects.
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Beginners
Those without any background in quantum computing may find the concepts and algorithms too advanced for comprehension.
Product Description
A Practical Guide to Quantum Machine Learning and Quantum Optimization: Hands-on Approach to Modern Quantum Algorithms
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Customer Questions & Answers
-
Question:
What prior knowledge do I need to start this book?
Answer: A basic understanding of linear algebra and some programming skills, preferably in Python, are recommended. -
Question:
Can I use this book for real-world applications?
Answer: Yes, the book covers practical examples and algorithms that can be applied to solve real-world optimization problems. -
Question:
What programming tools will I learn to use?
Answer: You will learn to use IBM's Qiskit, Xanadu's PennyLane, and D-Wave's Leap for implementing quantum algorithms.
Python Editorial Review
**** “A Practical Guide to Quantum Machine Learning and Quantum Optimization,” authored by Elías F. Combarro and Samuel González-Castillo, emerges as a significant contribution to the field of quantum computing literature, especially for those with an interest in algorithms and practical applications. Drawing from the success of a transformative online course, this book serves both novices and experts with a carefully structured pedagogical approach. Readers appreciate the authors' dedication to clarity and engagement. The book is commended for its systematic breakdown of complex topics, including an emphasis on practical algorithm implementation that can significantly aid comprehension. The unique feature of the book is its focus on modern quantum algorithms, particularly in quantum optimization and quantum machine learning, bridging theory with real-world coding through examples and exercises. Key functionalities include important study notes, supplementary resources for deeper learning, and a collection of exercises that enhance understanding. The integration of PennyLane as a programming framework stands out, granting users exposure to a flexible tool for quantum computing applications. Reviewers highlight that the coding exercises allow readers to experience quantum computing through hands-on practice, fostering a deeper understanding of fundamental concepts and their applications. The book's layout is designed for accessibility: sections can serve educational purposes independently or as a comprehensive course on advanced quantum algorithms. Many have found it indispensable as both a learning tool and a desk reference for ongoing work in the field. Readers recommend this book unequivocally for anyone looking to enhance their knowledge and skills in quantum computing and machine learning, indicating that it meets and exceeds expectations set during the initial online lectures. **
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Pros
- Comprehensive coverage of quantum algorithms particularly in optimization and machine learning
- Engaging and clear pedagogical style
- Plenty of practical exercises, with answers provided
- Use of the PennyLane programming framework, noted for inter-operability
- Ideal for both self-study and guided courses
- Appendices that aid in quick understanding of necessary mathematical concepts
Cons
- Basic concepts such as quantum teleportation and certain canonical algorithms may be excluded
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DKK 507
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Features & Benefits
- Hands-on approach to modern quantum algorithms.
- Minimal mathematical prerequisites required.
- Learn to solve real-world problems with practical examples.
- Utilize programming frameworks like Qiskit and PennyLane.
- Build a solid foundation in quantum computing fundamentals.
- Gain skills to implement quantum machine learning models.
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