Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Know how to use quantum computing solutions involving artificial intelligence (AI) algorithms and applications across different disciplines. Quantum solutions involve building quantum algorithms that improve computational tasks within quantum computing, AI, data science, and machine learning. As opposed to quantum computer innovation, quantum solutions offer automation, cost reduction, and other efficiencies to the problems they tackle. Starting with the basics, this book covers subsystems and properties as well as the information processing network before covering quantum simulators. Solutions such as the Traveling Salesman Problem, quantum cryptography, scheduling, and cybersecurity are discussed in step-by-step detail. The book presents code samples based on real-life problems in a variety of industries, such as risk assessment and fraud detection in banking. In pharma, you will look at drug discovery and protein-folding solutions. Supply chain optimization and purchasing solutions are presented in the manufacturing domain. In the area of utilities, energy distribution and optimization problems and solutions are explained. Advertising scheduling and revenue optimization solutions are included from media and technology verticals. You will: Understand the mathematics behind quantum computing Know the solution benefits, such as automation, cost reduction, and efficiencies Be familiar with the quantum subsystems and properties, including states, protocols, operations, and transformations Be aware of the quantum classification algorithms: classifiers, and support and sparse support vector machines Use AI algorithms, including probability, walks, search, deep learning, and parallelism.

Big data. --- Python (Computer program language). --- Quantum computers. --- Big Data. --- Python. --- Quantum Computing. --- Computers --- Scripting languages (Computer science) --- Data sets, Large --- Large data sets --- Data sets --- Quantum computing. --- Python (Computer program language) --- Computation, Quantum --- Computing, Quantum --- Information processing, Quantum --- Quantum computation --- Quantum information processing --- Electronic data processing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Explore Golang's data structures and algorithms to design, implement, and analyze code in the professional setting Key Features Learn the basics of data structures and algorithms and implement them efficiently Use data structures such as arrays, stacks, trees, lists and graphs in real-world scenarios Compare the complexity of different algorithms and data structures for improved code performance Book Description Golang is one of the fastest growing programming languages in the software industry. Its speed, simplicity, and reliability make it the perfect choice for building robust applications. This brings the need to have a solid foundation in data structures and algorithms with Go so as to build scalable applications. Complete with hands-on tutorials, this book will guide you in using the best data structures and algorithms for problem solving. The book begins with an introduction to Go data structures and algorithms. You'll learn how to store data using linked lists, arrays, stacks, and queues. Moving ahead, you'll discover how to implement sorting and searching algorithms, followed by binary search trees. This book will also help you improve the performance of your applications by stringing data types and implementing hash structures in algorithm design. Finally, you'll be able to apply traditional data structures to solve real-world problems. By the end of the book, you'll have become adept at implementing classic data structures and algorithms in Go, propelling you to become a confident Go programmer. What you will learn Improve application performance using the most suitable data structure and algorithm Explore the wide range of classic algorithms such as recursion and hashing algorithms Work with algorithms such as garbage collection for efficient memory management Analyze the cost and benefit trade-off to identify algorithms and data structures for problem solving Explore techniques for writing pseudocode algorithm and ace whiteboard coding in interviews Discover the pitfalls in selecting data structures and algorithms by predicting their speed and efficiency Who this book is for This book is for developers who want to understand how to select the best data structures and algorithms that will help solve coding problems. Basic Go programming experience will be an added advantage.

Data structures (Computer science)