Quantum Learning
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Quantum Learning
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Author : Bobbi DePorter
language : en
Publisher: Random House of Canada
Release Date : 1992
Quantum Learning written by Bobbi DePorter and has been published by Random House of Canada this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Education categories.
Identifies different learning styles and offers strategies for increasing learning potential and improving memory skills
Quantum Learning Beyond Duality
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Author : Conrad P. Pritscher
language : en
Publisher: Rodopi
Release Date : 2001
Quantum Learning Beyond Duality written by Conrad P. Pritscher and has been published by Rodopi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Education categories.
This book shows quantum learning is the resource that unites parts into wholes and then wholes into continually larger wholes. Just as quantum computers can regard sub-atomic particles as a wave and as particles, quantum learning can understand learners as simultaneously nondual (whole) and dual (part). The study includes a reconsideration of clarity in expression and thought
Machine Learning With Quantum Computers
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Author : Maria Schuld
language : en
Publisher: Springer Nature
Release Date : 2021-10-17
Machine Learning With Quantum Computers written by Maria Schuld and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-17 with Science categories.
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 level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.
Supervised Learning With Quantum Computers
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Author : Maria Schuld
language : en
Publisher: Springer
Release Date : 2018-08-30
Supervised Learning With Quantum Computers written by Maria Schuld and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-30 with Science categories.
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 topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.
Machine Learning Meets Quantum Physics
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Author : Kristof T. Schütt
language : en
Publisher: Springer Nature
Release Date : 2020-06-03
Machine Learning Meets Quantum Physics written by Kristof T. Schütt and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-03 with Science categories.
Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.
Quantum Machine Learning An Applied Approach
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Author : Santanu Ganguly
language : en
Publisher: Apress
Release Date : 2021-08-11
Quantum Machine Learning An Applied Approach written by Santanu Ganguly and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-11 with Computers categories.
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 advanced QML algorithms (quantum k-means, quantum k-medians, quantum neural networks, etc.), qubit state preparation for specific QML algorithms, inference, polynomial Hamiltonian simulation, and more, finishing with advanced and up-to-date research areas such as quantum walks, QML via Tensor Networks, and QBoost. Hands-on exercises from open source libraries regularly used today in industry and research are included, such as Qiskit, Rigetti's Forest, D-Wave's dOcean, Google's Cirq and brand new TensorFlow Quantum, and Xanadu's PennyLane, accompanied by guided implementation instructions. Wherever applicable, the book also shares various options of accessing quantum computing and machine learning ecosystems as may be relevant to specific algorithms. The book offers a hands-on approach to the field of QML using updated libraries and algorithms in this emerging field. You will benefit from the concrete examples and understanding of tools and concepts for building intelligent systems boosted by the quantum computing ecosystem. This work leverages the author’s active research in the field and is accompanied by a constantly updated website for the book which provides all of the code examples. What You will Learn Understand and explore quantum computing and quantum machine learning, and their application in science and industry Explore various data training models utilizing quantum machine learning algorithms and Python libraries Get hands-on and familiar with applied quantum computing, including freely available cloud-based access Be familiar with techniques for training and scaling quantum neural networks Gain insight into the application of practical code examples without needing to acquire excessive machine learning theory or take a quantum mechanics deep dive Who This Book Is For Data scientists, machine learning professionals, and researchers
Quantum Learning Instructional Leadership In Practice
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Author : John Parks Le Tellier
language : en
Publisher: Corwin Press
Release Date : 2006-10-27
Quantum Learning Instructional Leadership In Practice written by John Parks Le Tellier and has been published by Corwin Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-27 with Education categories.
Using evidence-based strategies, this inspiring handbook provides principals and teachers with a catalog of practiced "moves," or actions that upgrade performance, create durable motivation, and renew energy levels.
Icecem 2022
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Author : Mohammad Roqib
language : en
Publisher: European Alliance for Innovation
Release Date : 2023-12-11
Icecem 2022 written by Mohammad Roqib and has been published by European Alliance for Innovation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-11 with Education categories.
International Conference on Islamic Early Childhood Education in Multiperspectives (ICECEM) 2022 is a program of the Early Childhood Education study program at Prof.KH Saifuddin Zuhri Purwokerto State Islamic University. Aims to encourage and provide opportunities for researchers and academics to exchange views and opinions, answer and debate policy-relevant issues, and produce academic research outputs on important topics. The basic idea to encourage research in linguistics is to have maximum research impact on education, Islam, science, socio-culture, humanity, technology and digital.
Learn Quantum Computing With Python And Q
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Author : Sarah C. Kaiser
language : en
Publisher: Simon and Schuster
Release Date : 2021-07-27
Learn Quantum Computing With Python And Q written by Sarah C. Kaiser and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-27 with Computers categories.
Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Summary Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you’ll build your own quantum simulator and apply quantum programming techniques to real-world examples including cryptography and chemical analysis. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Quantum computers present a radical leap in speed and computing power. Improved scientific simulations and new frontiers in cryptography that are impossible with classical computing may soon be in reach. Microsoft’s Quantum Development Kit and the Q# language give you the tools to experiment with quantum computing without knowing advanced math or theoretical physics. About the book Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Use Python to build your own quantum simulator and take advantage of Microsoft’s open source tools to fine-tune quantum algorithms. The authors explain complex math and theory through stories, visuals, and games. You’ll learn to apply quantum to real-world applications, such as sending secret messages and solving chemistry problems. What's inside The underlying mechanics of quantum computers Simulating qubits in Python Exploring quantum algorithms with Q# Applying quantum computing to chemistry, arithmetic, and data About the reader For software developers. No prior experience with quantum computing required. About the author Dr. Sarah Kaiser works at the Unitary Fund, a non-profit organization supporting the quantum open-source ecosystem, and is an expert in building quantum tech in the lab. Dr. Christopher Granade works in the Quantum Systems group at Microsoft, and is an expert in characterizing quantum devices. Table of Contents PART 1 GETTING STARTED WITH QUANTUM 1 Introducing quantum computing 2 Qubits: The building blocks 3 Sharing secrets with quantum key distribution 4 Nonlocal games: Working with multiple qubits 5 Nonlocal games: Implementing a multi-qubit simulator 6 Teleportation and entanglement: Moving quantum data around PART 2 PROGRAMMING QUANTUM ALGORITHMS IN Q# 7 Changing the odds: An introduction to Q# 8 What is a quantum algorithm? 9 Quantum sensing: It’s not just a phase PART 3 APPLIED QUANTUM COMPUTING 10 Solving chemistry problems with quantum computers 11 Searching with quantum computers 12 Arithmetic with quantum computers
Proceedings Of The International Conference On Education Humanities And Social Science Icehos 2023
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Author : Dhea Adhela
language : en
Publisher: Springer Nature
Release Date : 2024-05-15
Proceedings Of The International Conference On Education Humanities And Social Science Icehos 2023 written by Dhea Adhela and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-15 with Education categories.
This is an open access book. Welcome to the 3rd International Conference on Education, Humanities, and Social Science – a prestigious gathering of thought leaders, academics, researchers, educators, and practitioners from diverse corners of the globe. With great enthusiasm, we extend our warmest invitation to all participants to join us in this intellectually stimulating event, held with the theme of “Fostering Global Connectivity: Transforming Education, Advancing Humanities, and Embracing Social Sciences.” In an increasingly interconnected world, the significance of education, humanities, and social sciences in shaping the trajectory of societies cannot be overstated. This conference serves as a dynamic platform for exchanging innovative ideas, research findings, and best practices that inspire positive change and sustainable development. Together, we aim to explore cutting-edge approaches in education, delve into the transformative power of humanities, and understand the complexities of the social sciences, all with the common goal of fostering greater global connectivity. By fostering interdisciplinary dialogue and collaboration, we seek to pave the way for impactful initiatives that address pressing challenges and embrace the rich diversity that characterizes our global community. We believe that through shared knowledge and collective efforts, we can collectively drive positive change and make a meaningful impact on the world we live in.