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  • Sách/Book


  • Authors: Parkin, Michael (2022)

  • The 14th Edition emphasizes real-worldapplications, the development of critical-thinking skills, diagrams renownedfor their pedagogy and clarity, and path-breaki

  • Sách/Book


  • Authors: Riley, Tim (2022)

  • Chapter 1: The Economic Problem. Chapter 2: The Operation of an Economy. Chapter 3: Economies: Their Similarities and Differences

  • Sách/Book


  • Authors: Venkatachalam, Ragupathy (2022)

  • This book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought.

  • Sách/Book


  • Authors: Chip Huyen (2022)

  • Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives

  • Sách/Book


  • Authors: Houneida Sakly (2022)

  • This book aims to present the impact of Artificial Intelligence (AI) and Big Data in healthcare for medical decision making and data analysis in myriad fields including Radiology, Radiomics, Radiogenomics, Oncology, Pharmacology, COVID-19 prognosis, Cardiac imaging, Neuroradiology, Psychiatry and others.

  • Sách/Book


  • Authors: Ghita K. Mostefaoui (2022)

  • Artificial Intelligence (AI) in general and machine learning (ML) and deep learning (DL) in particular and related digital technologies are a couple of fledging paradigms that the next generation healthcare services are sprouting towards. These digital technologies can transform various aspects of healthcare, leveraging advances in computing and communication power. With a new spectrum of business opportunities, AI-powered healthcare services would improve the lives of patients, their families, and societies. However, the application of AI in the healthcare field requires special attention given the direct implication with human life and well-being. Rapid progress in AI leads to the possibility of exploiting healthcare data for designing practical tools for automated diagnosis of ch...