Author : Bobbi DePorter
Publisher : Random House of Canada
Page : 355 pages
File Size : 39,42 MB
Release : 1992
Category : Education
ISBN : 9780440504276
Identifies different learning styles and offers strategies for increasing learning potential and improving memory skills
Author : Conrad P. Pritscher
Publisher : BRILL
Page : 224 pages
File Size : 50,50 MB
Release : 2021-11-08
Category : Philosophy
ISBN : 9004494073
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
Author : Maria Schuld
Publisher : Springer
Page : 293 pages
File Size : 12,77 MB
Release : 2018-08-30
Category : Science
ISBN : 3319964240
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.
Author : Barbara K. Given
Publisher :
Page : pages
File Size : 42,94 MB
Release : 2015-01-20
Category :
ISBN : 9780986300509
Author : Maria Schuld
Publisher : Springer Nature
Page : 321 pages
File Size : 10,8 MB
Release : 2021-10-17
Category : Science
ISBN : 3030830985
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.
Author : Bobbi DePorter
Publisher : Pearson
Page : 252 pages
File Size : 36,70 MB
Release : 1999
Category : Education
ISBN :
Now there's a better way to teach anything to anybody! Announcing...Quantum Teaching: Orchestrating Student Success Based on 18 years experience and research with over 25,000 students. Boosts teachers' ability to inspire and students' ability to achieve. This body of knowledge and methodology was first used at SuperCamp, an accelerated Quantum Learning program that achieved outstanding results for students. Quantum Teaching shows teachers how to orchestrate their students' success by taking into account everything in the classroom along with the environment, the design of the curriculum, and how it's presented. The result: a highly-effective way to teach anything to anybody!Available as an illustrated how-to book that bridges the gap between theory and practice and that covers today's hottest topics, like multiple intelligences, this book provides specific, easy-to-follow guidelines for creating more-effective learning environments, better ways to design curricula, and more interesting ways to deliver content and facilitate the learning process. Designed and written as an interactive tool, Quantum Teaching includes lesson planning guidelines to help teachers cover all the bases, without having to culminate different theories or refer to different source materials. A reproducible lesson planning guide makes it easy to start implementing new strategies immediately. Bobbi DePorter, author of the best-selling books Quantum Learning and Quantum Business, is founder and president of Learning Forum, which has helped over 25,000 students of all ages. Mark Reardon, a former teacher and principal, is an internationally recognized lead facilitator for Learning Forum. Sarah Singer-Nouri is an award-winning teacher and trainer.
Author : Peter Wittek
Publisher : Academic Press
Page : 176 pages
File Size : 43,46 MB
Release : 2014-09-10
Category : Science
ISBN : 0128010991
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 body of research. Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications. Bridges the gap between abstract developments in quantum computing with the applied research on machine learning Provides the theoretical minimum of machine learning, quantum mechanics, and quantum computing Gives step-by-step guidance to a broader understanding of this emergent interdisciplinary body of research
Author : Conrad P. Pritscher
Publisher : Rodopi
Page : 220 pages
File Size : 49,17 MB
Release : 2001
Category : Education
ISBN : 9789042013872
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
Author : Sarah C. Kaiser
Publisher : Simon and Schuster
Page : 545 pages
File Size : 11,93 MB
Release : 2021-07-27
Category : Computers
ISBN : 1638350906
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
Author : Frank Zickert
Publisher : Independently Published
Page : 440 pages
File Size : 38,66 MB
Release : 2021-06-19
Category :
ISBN :
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 is it fundamentally different and asks us to change the way we think. Hands-On Quantum Machine Learning With Python strives to be the perfect balance between theory taught in a textbook and the actual hands-on knowledge you'll need to implement real-world solutions. Inside this book, you will learn the basics of quantum computing and machine learning in a practical and applied manner.
