Machine Learning in Python for Process Systems Engineering : Achieve Operational Excellence Using Process DataКНИГИ » ПРОГРАММИНГ
Название: Machine Learning in Python for Process Systems Engineering: Achieve Operational Excellence Using Process Data Автор: Ankur Kumar, Jesus Flores-Cerrillo Издательство: Leanpub Год: 2022-02-17 Страниц: 352 Язык: английский Формат: pdf (true) Размер: 18.1 MB
This book provides a guided tour along the wide range of ML methods that have proven useful in process industry. Step-by-step instructions, supported with real process datasets, show how to develop ML-based solutions for process monitoring, predictive maintenance, fault diagnosis, soft sensing, and process control
This book provides an application-focused exposition of modern ML tools that have proven useful in process industry and hands-on illustrations on how to develop ML-based solutions for process monitoring, predictive maintenance, fault diagnosis, inferential modeling, dimensionality reduction, and process control. This book considers unique characteristics of industrial process data and uses real data from industrial systems for illustrations. With the focus on practical implementation and minimal programming or ML prerequisites, the book covers the gap in available ML resources for industrial practitioners. The authors of this book have drawn from their years of experience in developing data-driven industrial solutions to provide a guided tour along the wide range of available ML methods and declutter the world of machine learning. The readers will find all the resources they need to deal with high-dimensional, correlated, noisy, corrupted, multimode, and nonlinear process data.
The book has been divided into four parts. Part 1 provides a perspective on the importance of ML in process systems engineering and lays down the basic foundations of ML. Part 2 provides in-detail presentation of classical ML techniques and has been written keeping in mind the various characteristics of industrial process systems. Part 3 is focused on artificial neural networks and deep learning. Part 4 covers the important topic of deploying ML solutions over web and shows how to build a production-ready process monitoring web application.
Broadly, the book covers the following
Varied applications of ML in process industry Fundamentals of machine learning workflow Practical methodologies for pre-processing industrial data Classical ML methods and their application for process monitoring, fault diagnosis, and soft sensing Deep learning and its application for predictive maintenance Reinforcement learning and its application for process control Deployment of ML solution over web
Скачать Machine Learning in Python for Process Systems Engineering : Achieve Operational Excellence Using Process Data
Уважаемый посетитель, Вы зашли на сайт как незарегистрированный пользователь.
С этой публикацией часто скачивают:
Process Safety and Big Data Название: Process Safety and Big Data Автор: Sagit Valeev, Natalya Kondratyeva Издательство: Elsevier Год: 2021 Формат: PDF Страниц: 307 Размер:...
Spatial Predictive Modelling with R Название: Spatial Predictive Modelling with R Автор: Jin Li Издательство: CRC Press Год: 2022 Формат: PDF Страниц: 404 Размер: 75 Mb Язык: English ...
Metaheuristic Algorithms in Industry 4.0 Название: Metaheuristic Algorithms in Industry 4.0 Автор: Pritesh Shah, Ravi Sekhar, Anand J. Kulkarni Издательство: CRC Press Год: 2022 Страниц: 301...
Machine Learning for Cyber Physical Systems 2019 Название: Machine Learning for Cyber Physical Systems 2019 Автор: Jurgen Beyerer, Christian Kuhnert Издательство: Springer Vieweg ISBN: 3662584840...
Навигация
Вход на сайт
Реклама
Machine Learning in Python for Process Systems Engineering : Achieve Operational Excellence Using Process Data 
Название: Machine Learning in Python for Process Systems Engineering: Achieve Operational Excellence Using Process Data
