الصفحة 1
الصفحة 1
Designing machine learning systems : An iterative process for production-ready applications
Machine learning systems are both complex and unique. 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. The iterative framework in this book uses actual case studies backed by ample references. The book will help you tackle scenarios such as: Engineering data and choosing the right metrics to solve a business problem Automating the process for continually developing, evaluating, deploying, and updating models Developing a monitoring system to quickly detect and address issues your models might encounter in production Architecting an ML platform that serves across use cases Developing responsible ML systems
Computer Supported Cooperative Work in Design III ; 10th International Conference, CSCWD 2006, Nanjing, China, May 3-5, 2006, Revised Selected Papers
The design of complex artifacts and systems requires the cooperation of multidiscip- nary design teams using multiple commercial and proprietary engineering software tools (e.g., CAD, modeling, simulation, visualization, and optimization), engineering databases, and knowledge-based systems. Individuals or individual groups of mult- isciplinary design teams usually work in parallel and separately with various en- neering software tools which are located at different sites. In addition, individual members may be working on different versions of a design or viewing the design from different perspectives, at different levels of detail. In order to accomplish the work, it is necessary to have effective and efficient c- laborative design environments. Such environments should not only automate in- vidual tasks, in the manner of traditional computer-aided engineering tools, but also enable individual members to share information, collaborate, and coordinate their activities within the context of a design project. CSCW (computer-supported coope- tive work) in design is concerned with the development of such environments.
Computer Supported Cooperative Work in Design I
The design of complex artifacts and systems requires the cooperation of multidisciplinary design teams using multiple commercial and non-commercial engineering tools such as CAD tools, modeling, simulation and optimization software, engineering databases, and knowledge-based systems. Individuals or individual groups of multidisciplinary design teams usually work in parallel and separately with various engineering tools, which are located on different sites, often for quite a long time. At any moment, individual members may be working on different versions of a design or viewing the design from various perspectives, at different levels of detail. In order to meet these requirements, it is necessary to have effective and efficient collaborative design environments. These environments should not only automate individual tasks, in the manner of traditional computer-aided engineering tools, but also enable individual members to share information, collaborate and coordinate their activities within the context of a design project. CSCW (computer-supported cooperative work) in design is concerned with the development of such environments.
Knowledge and Skill Chains in Engineering and Manufacturing : Information Infrastructure in the Era of Global Communications
Explores knowledge and skill chains in engineering and manufacturing in the age of global communications. Information infrastructure involves a range of activities from product planning, engineering, and manufacturing trough transportation, marketing, and repair/upgrade to returns and recycling/disposal. Distinct from the traditional engineering database, life-cycle support information has its own characteristic requirements, -- flexible extensibility, distributed architecture, multiple viewpoints, long-time archiving, and product usage information. Several authors address the architecture of the information infrastructure, its services and its requirements. Other papers focus on the knowledge and skill chains that develop in a variety of situations: the supply chain, the factory floor, the man-system interaction, etc. For each of these, state-of-the-art and state-of-research scenarios for various industrial sectors address both engineering and operations requirements in the current socio-economic environment.
