Quantum Machine Learning: An Applied Approach
The Theory and Application of Quantum Machine Learning in Science and Industry
Price | $48.75 - $56.05
|
Rating | |
Author | Santanu Ganguly |
Publisher | Apress |
Published | 2021 |
Pages | 551 |
Language | English |
Format | Paper book / ebook (PDF) |
ISBN-10 | 1484270975 |
ISBN-13 | 9781484270974 |
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.
- Santanu Ganguly
5 5 4
Similar Books
Quantum Machine Learning and Optimisation in Finance
by Antoine Jacquier, Oleksiy Kondratyev
With recent advances in quantum computing technology, we finally reached the era of Noisy Intermediate-Scale Quantum (NISQ) computing. NISQ-era quantum computers are powerful enough to test quantum computing algorithms and solve hard real-world problems faster than classical hardware.Speedup is so important in financial applications, rang...
Price: $35.99 | Publisher: Packt Publishing | Release: 2022
by Nick Pentreath
Apache Spark is a framework for distributed computing that is designed from the ground up to be optimized for low latency tasks and in-memory data storage. It is one of the few frameworks for parallel computing that combines speed, scalability, in-memory processing, and fault tolerance with ease of programming and a flexible, expressive, ...
Price: $34.99 | Publisher: Packt Publishing | Release: 2015
Hands-On Machine Learning with C++
by Kirill Kolodiazhnyi
C++ can make your machine learning models run faster and more efficiently. This handy guide will help you learn the fundamentals of machine learning (ML), showing you how to use C++ libraries to get the most out of your data. This book makes machine learning with C++ for beginners easy with its example-based approach, demonstrating how to...
Price: $31.19 | Publisher: Packt Publishing | Release: 2020
Machine Learning with PyTorch and Scikit-Learn
by Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili
Machine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and examples, the book covers all the...
Price: $40.00 | Publisher: Packt Publishing | Release: 2022
Quantum Machine Learning with Python
by Santanu Pattanayak
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 lea...
Price: $28.98 | Publisher: Apress | Release: 2021
by Jeffrey Jackovich, Ruze Richards
Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are...
Price: $34.99 | Publisher: Packt Publishing | Release: 2018
Python Machine Learning, 3rd Edition
by Sebastian Raschka, Vahid Mirjalili
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and working examples, the book covers all the...
Price: $35.99 | Publisher: Packt Publishing | Release: 2019
by Yoon Hyup Hwang
Machine learning is applied in almost all kinds of real-world surroundings and industries, right from medicine to advertising; from finance to scientifc research. This book will help you learn how to choose a model for your problem, how to evaluate the performance of your models, and how you can use C# to build machine learning models for...
Price: $41.63 | Publisher: Packt Publishing | Release: 2018