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Automated Machine Learning
Get to grips with automated machine learning and adopt a hands-on approach to AutoML implementation and associated methodologies Key FeaturesGet up to speed with AutoML using OSS, Azure, AWS, GCP, or any platform of your choiceEliminate mundane tasks in data engineering and reduce human errors in machine learning modelsFind out how you can make machine learning accessible for all users to promote decentralized processesBook Description Every machine learning engineer deals with systems that have hyperparameters, and the most basic task in automated machine learning (AutoML) is to automatically set these hyperparameters to optimize performance. The latest deep neural networks have a wide rang...
Strategizing AI in Business and Education
This Element proposes a clear and up-to-date description of the state of artificial intelligence today, not only in terms of business processes and strategies, but also its societal reception. It presents our view of the technology landscape, avoiding both the forward-looking, rose-colored utopia and the hyper-apocalyptic gloom. It does so in a concise form, addressing a complex issue in 9 concise and easy-to-read chapters. It aims to discuss the current state of machine learning and AI in strategic management, and to describe the emerging technologies. It conceptualizes their adoption, and then consider the effects of AI technologies' maturity in business organizations.
Responsible AI in the Enterprise
Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfalls Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn ethical AI principles, frameworks, and governance Understand the concepts of fairness assessment and bias mitigation Introduce explainable AI and transparency in your machine learning models Book DescriptionResponsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as...
Arts: A Science Matter
This book treats arts as part of science, from the unified perspective of Science Matters. It contains 17 chapters, with 18 contributors who are prominent humanists, professional artists, or scientists. It consists of three parts: Part I: Philosophy and History of Arts; Part II: Arts in Action; Part III: Understanding Arts. The book is aimed at both research scholars and laypeople, and is unique in two important aspects. It is probably the first and only book that academic professionals and practicing artists contribute to the same book, as equals, on the common theme of creating and understanding arts. (Artists here include Cristina Leiria whose huge Kun Iam (Goddess of Mercy) sculpture is an important landmark in Macau, and the famous movie director, Hark Tsui, who is publishing his first ever article on movie-making). Perhaps more importantly, a new understanding of the origin and nature of arts is offered for the first time, which is more convincing than all the other hypotheses put forth in the last two thousand years.
Conversational Artificial Intelligence
This book reviews present state-of-the-art research related to the security of cloud computing including developments in conversational AI applications. It is particularly suited for those that bridge the academic world and industry, allowing readers to understand the security concerns in advanced security solutions for conversational AI in the cloud platform domain by reviewing present and evolving security solutions, their limitations, and future research directions. Conversational AI combines natural language processing (NLP) with traditional software like chatbots, voice assistants, or an interactive voice recognition system to help customers through either a spoken or typed interface. C...
Learning F# Functional Data Structures and Algorithms
F# is a multi-paradigm programming language that encompasses object-oriented, imperative, and functional programming language properties. The F# functional programming language enables developers to write simple code to solve complex problems. Starting with the fundamental concepts of F# and functional programming, this book will walk you through basic problems, helping you to write functional and maintainable code. Using easy-to-understand examples, you will learn how to design data structures and algorithms in F# and apply these concepts in real-life projects. The book will cover built-in data structures and take you through enumerations and sequences. You will gain knowledge about stacks, graph-related algorithms, and implementations of binary trees. Next, you will understand the custom functional implementation of a queue, review sets and maps, and explore the implementation of a vector. Finally, you will find resources and references that will give you a comprehensive overview of F# ecosystem, helping you to go beyond the fundamentals.
Hands-On Genetic Algorithms with Python
Explore the ever-growing world of genetic algorithms to build and enhance AI applications involving search, optimization, machine learning, deep learning, NLP, and XAI using Python libraries Key Features Learn how to implement genetic algorithms using Python libraries DEAP, scikit-learn, and NumPy Take advantage of cloud computing technology to increase the performance of your solutions Discover bio-inspired algorithms such as particle swarm optimization (PSO) and NEAT Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by Eyal Wirsansky, a senior data scientist and AI researcher with over 25 years of experience and a research background in genetic algorith...
Apache Spark Deep Learning Cookbook
A solution-based guide to put your deep learning models into production with the power of Apache Spark Key Features Discover practical recipes for distributed deep learning with Apache Spark Learn to use libraries such as Keras and TensorFlow Solve problems in order to train your deep learning models on Apache Spark Book Description With deep learning gaining rapid mainstream adoption in modern-day industries, organizations are looking for ways to unite popular big data tools with highly efficient deep learning libraries. As a result, this will help deep learning models train with higher efficiency and speed. With the help of the Apache Spark Deep Learning Cookbook, you’ll work through spe...
