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- O'Reilly for Higher Education This link opens in a new windowIncludes books, interactive tutorials, and videos in computer science, information systems, user experience, business, communication, professional development, and management topics.
IoT Technologies in Smart-Cities by
Smart City and sensing platforms are considered some of the most significant topics in the Internet of Things (IoT). Sensors are at the heart of the IoT, and their development is a key issue if such concepts are to achieve their full potential. This book addresses the major challenges in realizing smart city and sensing platforms in the era of the IoT and the Cloud. Challenges vary from cost and energy efficiency to availability and service quality. To tackle these challenges, sensors must meet certain expectations and requirements such as size constraints, manufacturing costs and resistance to environmental factors. This book focuses on both the design and implementation aspects for smart city and sensing applications that are enabled and supported by IoT paradigms. Attention is also given to data delivery approaches and performance aspects.
ISBN: 9781785618697Publication Date: 2020-06-09
Building Recommender Systems with Machine Learning and AI by
Automated recommendations are everywhere: Netflix, Amazon, YouTube, and more. Recommender systems learn about your unique interests and show the products or content they think you’ll like best. Discover how to build your own recommender systems from one of the pioneers in the field. Frank Kane spent over nine years at Amazon, where he led the development of many of the company’s personalized product recommendation technologies. In this course, he covers recommendation algorithms based on neighborhood-based collaborative filtering and more modern techniques, including matrix factorization and even deep learning with artificial neural networks. Along the way, you can learn from Frank's extensive industry experience and understand the real-world challenges of applying these algorithms at a large scale with real-world data. You can also go hands-on, developing your own framework to test algorithms and building your own neural networks using technologies like Amazon DSSTNE, AWS SageMaker, and TensorFlow.
Publication Date: 2020
System Lifecycle Management by
Years of experience in the area of Product Lifecycle Management (PLM) in industry, research and education form the basis for this overview. The author covers the development from PDM via PLM to SysLM (System Lifecycle Management) in the form commonly used today, which are necessary prerequisites for the sustainable development and implementation of IoT/IoS, Industry 4.0 and Engineering 4.0 concepts. The building blocks and properties of future-proof systems for the successful implementation of the concepts of Engineering 4.0 are thereby dedicated to holistic considerations, which also inform in detail. SysLM functions and processes in mechatronic development and design as well as across the entire product lifecycle - from requirements management to the Digital Twin - are covered as examples. SysLM trends such as low code development, cloud, disruptive business models, and bimodality provide an outlook on future developments. The author dedicates the treatment of the agile SysLM introduction to the implementation in the enterprise. The basics are deepened with examples of a concrete SysLM system.
ISBN: 9783658338732Publication Date: 2021-08-11
