Quantum Machine Learning: An Applied Approach
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 Qisk ...
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 Qisk ...
HackSpace Magazine: Issue 45
This issue we're paying homage to some of our favourite projects built on the Raspberry Pi. We're living in a golden age for experimentation, accessible making and digital discovery - and a large part of that is thanks to this teeny tiny computer. Just add imagination! - How one maker achieved perfection (yes, really!) by embracing failure; - Our pick of the best walking robot kits; - A deceptively simple hack for printing large objects (hint - you make the printer bigger); - Homebrew improvements to a cheap CNC machine; - How to put an oak handle on an old kitchen knife; - ... and loads more. ...
This issue we're paying homage to some of our favourite projects built on the Raspberry Pi. We're living in a golden age for experimentation, accessible making and digital discovery - and a large part of that is thanks to this teeny tiny computer. Just add imagination! - How one maker achieved perfection (yes, really!) by embracing failure; - Our pick of the best walking robot kits; - A deceptively simple hack for printing large objects (hint - you make the printer bigger); - Homebrew improvements to a cheap CNC machine; - How to put an oak handle on an old kitchen knife; - ... and loads more. ...
Linux Cookbook, 2nd Edition
This handy cookbook teaches new-to-intermediate Linux users the essential skills necessary to manage a Linux system, using both graphical and command-line tools. Whether you run Linux in embedded, desktop, server, or cloud or virtual environments, the fundamental skills are the same. This book aims to get you up and running quickly, with copy-paste examples. Carla Schroder provides recipes that cover specific problems, with discussions that explain how each recipe works, as well as references for additional study. You'll learn how to: Use systemd, the new comprehensive service manager; Build simple or complex firewalls with firewalld; Set up secure network connections for Linux systems and mobile devices; Rescue nonbooting systems; Reset lost passwords on Linux and Windows; Use dnsmasq to simplify managing your LAN name services; Manage users and groups and control access to files; Probe your computer hardware and monitor hardware health; Manage the GRUB bootloader and multiboot ...
This handy cookbook teaches new-to-intermediate Linux users the essential skills necessary to manage a Linux system, using both graphical and command-line tools. Whether you run Linux in embedded, desktop, server, or cloud or virtual environments, the fundamental skills are the same. This book aims to get you up and running quickly, with copy-paste examples. Carla Schroder provides recipes that cover specific problems, with discussions that explain how each recipe works, as well as references for additional study. You'll learn how to: Use systemd, the new comprehensive service manager; Build simple or complex firewalls with firewalld; Set up secure network connections for Linux systems and mobile devices; Rescue nonbooting systems; Reset lost passwords on Linux and Windows; Use dnsmasq to simplify managing your LAN name services; Manage users and groups and control access to files; Probe your computer hardware and monitor hardware health; Manage the GRUB bootloader and multiboot ...
React Cookbook
React helps you create and work on an app in just a few minutes. But learning how to put all the pieces together is hard. How do you validate a form? Or implement a complex multistep user action without writing messy code? How do you test your code? Make it reusable? Wire it to a backend? Keep it easy to understand? The React Cookbook delivers answers fast. Many books teach you how to get started, understand the framework, or use a component library with React, but very few provide examples to help you solve particular problems. This easy-to-use cookbook includes the example code developers need to unravel the most common problems when using React, categorized by topic area and problem. You'll learn how to: Build a single-page application in React using a rich UI; Create progressive web applications that users can install and work with offline; Integrate with backend services such as REST and GraphQL; Automatically test for accessibility problems in your application; Secure appli ...
React helps you create and work on an app in just a few minutes. But learning how to put all the pieces together is hard. How do you validate a form? Or implement a complex multistep user action without writing messy code? How do you test your code? Make it reusable? Wire it to a backend? Keep it easy to understand? The React Cookbook delivers answers fast. Many books teach you how to get started, understand the framework, or use a component library with React, but very few provide examples to help you solve particular problems. This easy-to-use cookbook includes the example code developers need to unravel the most common problems when using React, categorized by topic area and problem. You'll learn how to: Build a single-page application in React using a rich UI; Create progressive web applications that users can install and work with offline; Integrate with backend services such as REST and GraphQL; Automatically test for accessibility problems in your application; Secure appli ...
Java Notes for Professionals
The Java Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow. ...
The Java Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow. ...
Human-in-the-Loop Machine Learning
Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process. Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-Loop Machine Learning lays out methods for humans and machines to work together effectively. You'll find best pra ...
Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process. Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-Loop Machine Learning lays out methods for humans and machines to work together effectively. You'll find best pra ...
Own Your Tech Career
Whatever your road to success, you'll benefit from the toolbox of career-boosting techniques you'll find in Own Your Tech Career: Soft skills for technologists. You'll discover in-demand communication and teamwork skills, essential rules for professionalism, tactics of the modern job hunt, and more. A successful technology career demands more than just technical ability. Achieving your goals requires clear communication, top-notch time management, and a knack for navigating business needs. Master the "soft skills," and you'll have a smoother path to success and satisfaction, however you define that for yourself. Own Your Tech Career: Soft skills for technologists helps you get what you want out of your technology career. You'll start by defining your ambition - whether that's a salary, a job title, a flexible schedule, or something else. Once you know where you're going, this book's adaptable advice guides your journey. You'll learn conflict resolution and teamwork, master nine r ...
Whatever your road to success, you'll benefit from the toolbox of career-boosting techniques you'll find in Own Your Tech Career: Soft skills for technologists. You'll discover in-demand communication and teamwork skills, essential rules for professionalism, tactics of the modern job hunt, and more. A successful technology career demands more than just technical ability. Achieving your goals requires clear communication, top-notch time management, and a knack for navigating business needs. Master the "soft skills," and you'll have a smoother path to success and satisfaction, however you define that for yourself. Own Your Tech Career: Soft skills for technologists helps you get what you want out of your technology career. You'll start by defining your ambition - whether that's a salary, a job title, a flexible schedule, or something else. Once you know where you're going, this book's adaptable advice guides your journey. You'll learn conflict resolution and teamwork, master nine r ...
Good Code, Bad Code
The difference between good code or bad code often comes down to how you apply the established practices of the software development community. In Good Code, Bad Code you'll learn how to boost your productivity and effectiveness with code development insights normally only learned through careful mentorship and hundreds of code reviews. Software development is a team sport. For an application to succeed, your code needs to be robust and easy for others to understand, maintain, and adapt. Whether you're working on an enterprise team, contributing to an open source project, or bootstrapping a startup, it pays to know the difference between good code and bad code. Good Code, Bad Code is a clear, practical introduction to writing code that's a snap to read, apply, and remember. With dozens of instantly-useful techniques, you'll find coding insights that normally take years of experience to master. In this fast-paced guide, Google software engineer Tom Long teaches you a host of rules ...
The difference between good code or bad code often comes down to how you apply the established practices of the software development community. In Good Code, Bad Code you'll learn how to boost your productivity and effectiveness with code development insights normally only learned through careful mentorship and hundreds of code reviews. Software development is a team sport. For an application to succeed, your code needs to be robust and easy for others to understand, maintain, and adapt. Whether you're working on an enterprise team, contributing to an open source project, or bootstrapping a startup, it pays to know the difference between good code and bad code. Good Code, Bad Code is a clear, practical introduction to writing code that's a snap to read, apply, and remember. With dozens of instantly-useful techniques, you'll find coding insights that normally take years of experience to master. In this fast-paced guide, Google software engineer Tom Long teaches you a host of rules ...
Transfer Learning for Natural Language Processing
Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You'll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you'll save on training time and computational costs. Build custom NLP models in record time, even with limited datasets! Transfer learning is a machine learning technique for adapting pretrained machine learning models to solve specialized problems. This powerful approach has revolutionized natural language processing, driving improvements in machine translation, business analytics, and natural language generation. Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions ...
Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You'll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you'll save on training time and computational costs. Build custom NLP models in record time, even with limited datasets! Transfer learning is a machine learning technique for adapting pretrained machine learning models to solve specialized problems. This powerful approach has revolutionized natural language processing, driving improvements in machine translation, business analytics, and natural language generation. Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions ...
Deep Learning Patterns and Practices
The big challenge of deep learning lies in taking cutting-edge technologies from R&D labs through to production. Deep Learning Patterns and Practices is here to help. This unique guide lays out the latest deep learning insights from author Andrew Ferlitsch's work with Google Cloud AI. In it, you'll find deep learning models presented in a unique new way: as extendable design patterns you can easily plug-and-play into your software projects. Each valuable technique is presented in a way that's easy to understand and filled with accessible diagrams and code samples. Discover best practices, design patterns, and reproducible architectures that will guide your deep learning projects from the lab into production. This awesome book collects and illuminates the most relevant insights from a decade of real world deep learning experience. You'll build your skills and confidence with each interesting example. Deep Learning Patterns and Practices is a deep dive into building successful deep ...
The big challenge of deep learning lies in taking cutting-edge technologies from R&D labs through to production. Deep Learning Patterns and Practices is here to help. This unique guide lays out the latest deep learning insights from author Andrew Ferlitsch's work with Google Cloud AI. In it, you'll find deep learning models presented in a unique new way: as extendable design patterns you can easily plug-and-play into your software projects. Each valuable technique is presented in a way that's easy to understand and filled with accessible diagrams and code samples. Discover best practices, design patterns, and reproducible architectures that will guide your deep learning projects from the lab into production. This awesome book collects and illuminates the most relevant insights from a decade of real world deep learning experience. You'll build your skills and confidence with each interesting example. Deep Learning Patterns and Practices is a deep dive into building successful deep ...