menu
{ "item_title" : "Machine Learning for Cyber Physical Systems", "item_author" : [" Jürgen Beyerer", "Alexander Maier", "Oliver Niggemann "], "item_description" : "This open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments. ", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/66/262/745/3662627450_b.jpg", "price_data" : { "retail_price" : "49.99", "online_price" : "49.99", "our_price" : "49.99", "club_price" : "49.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning for Cyber Physical Systems|Jürgen Beyerer

Machine Learning for Cyber Physical Systems : Selected Papers from the International Conference Ml4cps 2020

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

This open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020.

Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.


This item is Non-Returnable

Details

  • ISBN-13: 9783662627457
  • ISBN-10: 3662627450
  • Publisher: Springer Vieweg
  • Publish Date: December 2020
  • Dimensions: 9.4 x 7.6 x 0.3 inches
  • Shipping Weight: 0.5 pounds
  • Page Count: 130

Related Categories

You May Also Like...

    1

BAM Customer Reviews