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  • TVS.005060_TT_Intelligent Network Design Driven by Big Data Analytics, IoT, AI and Cloud Computing-The Institution of Engineering and Technology (2.pdf.jpg
  • Sách/Book


  • Authors: Kumar, Sunil (2023)

  • This book will be useful to researchers, scientists, engineers, professionals, advanced students and faculty members in ICTs, data science, networking, AI, machine learning and sensing. It will also be of interest to professionals in data science, AI, cloud and IoT start-up companies, as well as developers and designers

  • TVS.005074_TT_(Texts in Computer Science) Tomas Hrycej, Bernhard Bermeitinger, Matthias Cetto, Siegfried Handschuh - Mathematical Foundations of Data.pdf.jpg
  • Sách/Book


  • Authors: Hrycej, Tomas (2023)

  • This textbook aims to point out the most important principles of data analysis from the mathematical point of view. Specifically, it selected these questions for exploring: Which are the principles necessary to understand the implications of an application, and which are necessary to understand the conditions for the success of methods used? Theory is presented only to the degree necessary to apply it properly, striving for the balance between excessive complexity and oversimplification. Its primary focus is on principles crucial for application success

  • TVS.006035_TT_Anthony Sarkis - Training Data for Machine Learning_ Human Supervision from Annotation to Data Science (8th Early release)-O_Reilly Medi.pdf.jpg
  • Sách/Book


  • Authors: Sarkis, Anthony (2023)

  • Training Data controls the system by defining the ground truth goals for the creation of Machine Learning models. This involves technical representations, people decisions, processes, tooling, system design, and a variety of new concepts specific to Training Data. In a sense, a Training Data mindset is a paradigm upon which a growing list of theories, research and standards are emerging. A Machine Learning (ML) Model that is created as the end result of a ML Training Process.