Programowanie
Hassi Norlen
IBM Quantum Experience® is a leading platform for programming quantum computers and implementing quantum solutions directly on the cloud. This book will help you get up to speed with programming quantum computers and provide solutions to the most common problems and challenges.You’ll start with a high-level overview of IBM Quantum Experience® and Qiskit®, where you will perform the installation while writing some basic quantum programs. This introduction puts less emphasis on the theoretical framework and more emphasis on recent developments such as Shor’s algorithm and Grover’s algorithm. Next, you’ll delve into Qiskit®, a quantum information science toolkit, and its constituent packages such as Terra, Aer, Ignis, and Aqua. You’ll cover these packages in detail, exploring their benefits and use cases. Later, you’ll discover various quantum gates that Qiskit® offers and even deconstruct a quantum program with their help, before going on to compare Noisy Intermediate-Scale Quantum (NISQ) and Universal Fault-Tolerant quantum computing using simulators and actual hardware. Finally, you’ll explore quantum algorithms and understand how they differ from classical algorithms, along with learning how to use pre-packaged algorithms in Qiskit® Aqua.By the end of this quantum computing book, you’ll be able to build and execute your own quantum programs using IBM Quantum Experience® and Qiskit® with Python.
Srinjoy Ganguly, Thomas Cambier
Quantum computing is a growing field, with many research projects focusing on programming quantum computers in the most efficient way possible. One of the biggest challenges faced with existing languages is that they work on low-level circuit model details and are not able to represent quantum programs accurately. Developed by researchers at ETH Zurich after analyzing languages including Q# and Qiskit, Silq is a high-level programming language that can be viewed as the C++ of quantum computers! Quantum Computing with Silq Programming helps you explore Silq and its intuitive and simple syntax to enable you to describe complex tasks with less code. This book will help you get to grips with the constructs of the Silq and show you how to write quantum programs with it. You’ll learn how to use Silq to program quantum algorithms to solve existing and complex tasks. Using quantum algorithms, you’ll also gain practical experience in useful applications such as quantum error correction, cryptography, and quantum machine learning. Finally, you’ll discover how to optimize the programming of quantum computers with the simple Silq.By the end of this Silq book, you’ll have mastered the features of Silq and be able to build efficient quantum applications independently.
Antoine Jacquier, Oleksiy Kondratyev, Alexander Lipton, Marcos...
As quantum machine learning (QML) continues to evolve, many professionals struggle to apply its powerful algorithms to real-world problems using noisy intermediate-scale quantum (NISQ) hardware. This book bridges that gap by focusing on hands-on QML applications tailored to NISQ systems, moving beyond the traditional textbook approaches that explore standard algorithms like Shor's and Grover's, which lie beyond current NISQ capabilities.You’ll get to grips with major QML algorithms that have been widely studied for their transformative potential in finance and learn hybrid quantum-classical computational protocols, the most effective way to leverage quantum and classical computing systems together.The authors, Antoine Jacquier, a distinguished researcher in quantum computing and stochastic analysis, and Oleksiy Kondratyev, a Quant of the Year awardee with over 20 years in quantitative finance, offer a hardware-agnostic perspective. They present a balanced view of both analog and digital quantum computers, delving into the fundamental characteristics of the algorithms while highlighting the practical limitations of today’s quantum hardware.By the end of this quantum book, you’ll have a deeper understanding of the significance of quantum computing in finance and the skills needed to apply QML to solve complex challenges, driving innovation in your work.
Jeremy Samuelson
Quantum computing is advancing rapidly, yet practical guidance for machine learning engineers remains limited. Most resources emphasize physics or theory, leaving practitioners unsure how quantum methods fit into real-world ML workflows. 'Quantum Machine Learning in Practice' addresses this gap with a hands-on, Python-first approach built for data scientists and ML engineers.Rather than presenting quantum models as replacements for classical ML, this book focuses on disciplined experimentation, hybrid architectures, and rigorous benchmarking. You will learn how classical data is encoded into quantum circuits, how variational models serve as classifiers and regressors, and how to evaluate quantum kernels and generative models responsibly. Concepts are grounded in simulator-based experiments using PennyLane, Qiskit, TensorFlow Quantum, and Cirq. Classical baselines are treated as first-class citizens throughout. You will design fair comparisons, analyze computational tradeoffs, and identify when classical ML remains superior. A complete end-to-end mini project reinforces transferable workflow skills, from problem framing through evaluation and interpretation.By the end, you will be able to design, implement, and critically assess hybrid quantum-classical machine learning systems with clarity and confidence.
Robert Loredo, Matt Broomhall
Prepare for a computing shift that will reshape security, optimization, and competitive advantage across every industry. This book helps you build a clear actionable approach to quantum readiness covering strategy, technology, talent, and risk in one framework.Written by Robert Loredo, Founder and CEO of Entangled Solutions Group, this book draws on 25 years of experience across IBM, academia, and enterprise innovation. As a former IBM Quantum Global Strategist, leader of the IBM Quantum Ambassador program, and holds over 275 patents, he translates this complex technology transition into decisions leaders can act on immediately.This book is organized as a complete strategic operating system for the quantum transition. Part One equips executives with investment frameworks, governance structures, and talent roadmaps. Part Two guides technical leaders through infrastructure assessment, workforce development, and quantum-era data strategy. Part Three delivers a security playbook covering post-quantum cryptography and adaptive architecture. Part Four maps the full quantum ecosystem and partnerships that will determine which institutions lead commercially.By the end, you’ll be able to define a quantum strategy, build the right capabilities, and lead your organization through quantum-driven change with clarity and control.
Quick Start Kubernetes. A Beginner's Guide to Container Orchestration in the Cloud - Third Edition
Nigel Poulton
This book is the backbone of modern cloud-native application deployment, but its complexity can be daunting for beginners. This book provides a practical and approachable guide to mastering Kubernetes, starting with fundamental concepts like microservices, orchestration, and cloud-native development. Readers will explore Kubernetes architecture, including control planes, worker nodes, and hosted solutions.Step-by-step instructions guide readers through setting up Kubernetes clusters on local and cloud platforms, containerizing applications, and pushing images to registries. Learn how to deploy containerized applications, connect them via services, and enable self-healing to ensure resilience.As you advance, discover how to scale applications dynamically, perform rolling updates for zero-downtime deployments, and troubleshoot real-world issues. The book concludes with resources for further learning, empowering readers to confidently manage Kubernetes environments in DevOps or cloud-native roles. Perfect for beginners, this hands-on guide simplifies Kubernetes for practical use.
Nigel Poulton
Begin with an introduction to Kubernetes, understanding its importance and architecture. These foundational chapters will set the stage for your exploration into Kubernetes' capabilities. As you progress, you'll learn how to set up Kubernetes and containerize an application, equipping you with practical skills for real-world application management.The course continues with a focus on running applications on Kubernetes, where you will delve into self-healing mechanisms, scaling, and performing rolling updates. Each chapter builds on the last, ensuring a seamless learning experience that integrates theoretical knowledge with hands-on practice. You'll understand how Kubernetes maintains application health and performance, providing a robust environment for modern applications.Concluding with advanced operational techniques and future steps, the course prepares you to leverage Kubernetes for continuous development and deployment. Whether you're scaling applications to meet demand or ensuring seamless updates with minimal downtime, you'll be equipped with the skills necessary for efficient and effective Kubernetes management. This course is your gateway to becoming proficient in one of the most essential tools in the DevOps toolkit.
Dan MacLean
The updated second edition of R Bioinformatics Cookbook takes a recipe-based approach to show you how to conduct practical research and analysis in computational biology with R. You’ll learn how to create a useful and modular R working environment, along with loading, cleaning, and analyzing data using the most up-to-date Bioconductor, ggplot2, and tidyverse tools.This book will walk you through the Bioconductor tools necessary for you to understand and carry out protocols in RNA-seq and ChIP-seq, phylogenetics, genomics, gene search, gene annotation, statistical analysis, and sequence analysis. As you advance, you'll find out how to use Quarto to create data-rich reports, presentations, and websites, as well as get a clear understanding of how machine learning techniques can be applied in the bioinformatics domain. The concluding chapters will help you develop proficiency in key skills, such as gene annotation analysis and functional programming in purrr and base R. Finally, you'll discover how to use the latest AI tools, including ChatGPT, to generate, edit, and understand R code and draft workflows for complex analyses.By the end of this book, you'll have gained a solid understanding of the skills and techniques needed to become a bioinformatics specialist and efficiently work with large and complex bioinformatics datasets.