TY - BOOK ID - 134654104 TI - Data Science for IoT Engineers : A Systems Analytics Approach. PY - 2021 SN - 1683926404 1683926412 PB - Bloomfield : Mercury Learning & Information, DB - UniCat KW - IOT. KW - MATLAB. KW - computer science. KW - data analytics. KW - engineering. KW - mathematics. KW - physics. UR - https://www.unicat.be/uniCat?func=search&query=sysid:134654104 AB - This book introduces the concepts of data science to professionals in engineering, physics, mathematics, and allied fields. It is a workbook with MATLAB code that creates a common framework and points out various interconnections related to industry. This will allow the reader to connect previous subject knowledge to data science, machine learning, or analytics and apply it to IoT applications. Part One brings together subjects in machine learning, systems theory, linear algebra, digital signal processing, and probability theory. Part Two (Systems Analytics) develops a “universal” nonlinear, time-varying dynamical machine learning solution that can faithfully model all the essential complexities of real-life business problems and shows how to apply it. FEATURES:Develops a “universal,” nonlinear, dynamical machine learning solution to model and apply the complexities of modern applications in IoTCovers topics such as machine learning, systems theory, linear algebra, digital signal processing, probability theory, state-space formulation, Bayesian estimation, Kalman filter, causality, and digital twins. ER -