Active Learning Engineering
Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation eBooks & eLearning
Posted by interes at May 17, 2013
Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation (Adaptive Computation and Machine Learning series) by Masashi Sugiyama and Motoaki Kawanabe
English | 2012 | ISBN: 0262017091 | ISBN-13: 9780262017091 | 280 pages | PDF | 12,1 MB
English | 2012 | ISBN: 0262017091 | ISBN-13: 9780262017091 | 280 pages | PDF | 12,1 MB
As the power of computing has grown over the past few decades, the field of machine learning has advanced rapidly in both theory and practice. Machine learning methods are usually based on the assumption that the data generation mechanism does not change over time.
Optimal Learning eBooks & eLearning
Posted by ChrisRedfield at Dec. 22, 2014
Warren B. Powell, Ilya O. Ryzhov - Optimal Learning
Published: 2012-04-17 | ISBN: 0470596694 | PDF | 404 pages | 20 MB
Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation (repost) eBooks & eLearning
Posted by libr at Oct. 26, 2015
Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation (Adaptive Computation and Machine Learning series) by Masashi Sugiyama and Motoaki Kawanabe
English | 2012 | ISBN: 0262017091 | ISBN-13: 9780262017091 | 280 pages | PDF | 12,1 MB
English | 2012 | ISBN: 0262017091 | ISBN-13: 9780262017091 | 280 pages | PDF | 12,1 MB
Learning with Uncertainty eBooks & eLearning
Posted by Underaglassmoon at Jan. 13, 2017
Learning with Uncertainty
CRC Press | English | December 2016 | ISBN-10: 1498724124 | 239 pages | PDF | 9.67 mb
CRC Press | English | December 2016 | ISBN-10: 1498724124 | 239 pages | PDF | 9.67 mb
by Xizhao Wang (Author), Junhai Zhai (Author)
Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation eBooks & eLearning
Posted by interes at March 25, 2019
Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation (Adaptive Computation and Machine Learning series) by Masashi Sugiyama and Motoaki Kawanabe
English | 2012 | ISBN: 0262017091 | ISBN-13: 9780262017091 | 280 pages | PDF | 12,1 MB
English | 2012 | ISBN: 0262017091 | ISBN-13: 9780262017091 | 280 pages | PDF | 12,1 MB
Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation eBooks & eLearning
Posted by step778 at March 11, 2019
Masashi Sugiyama, Motoaki Kawanabe, "Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation"
2012 | pages: 263 | ISBN: 0262017091 | DJVU | 2,2 mb
2012 | pages: 263 | ISBN: 0262017091 | DJVU | 2,2 mb
Optimal Learning eBooks & eLearning
Posted by arundhati at June 30, 2019
Warren B. Powell, "Optimal Learning"
English | ISBN: 0470596694 | 2012 | 404 pages | PDF | 21 MB
English | ISBN: 0470596694 | 2012 | 404 pages | PDF | 21 MB
Fundamentals and Applications of Colour Engineering eBooks & eLearning
Posted by yoyoloit at Oct. 16, 2023
Fundamentals and Applications of Colour Engineering
by Green, Phil;
English | 2023 | ISBN: 1119827183 | 400 pages | True PDF EPUB | 39.53 MB
by Green, Phil;
English | 2023 | ISBN: 1119827183 | 400 pages | True PDF EPUB | 39.53 MB
Machine Learning and Knowledge Discovery in Databases eBooks & eLearning
Posted by AvaxGenius at Feb. 24, 2021
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part II by Frank Hutter
English | PDF | 2021 | 770 Pages | ISBN : 3030676609 | 79.4 MB
The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic.
Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track eBooks & eLearning
Posted by AvaxGenius at Feb. 24, 2021
Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part IV by Yuxiao Dong
English | PDF | 2021 | 612 Pages | ISBN : 3030676668 | 55.8 MB
The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic.