Popular Post
-
I have got the comment on my previous post “ BIRT based Control Chart “ with questions about how actually in BIRT the data are prepared for ... -
Re-posting interesting article from R-vs.-Python-for-Data-Science R vs. Python for Data Science Norm Matloff, Prof. of Computer ...
Tuesday, September 15, 2020
My CMG Video presentation "Catching Anomaly and Normality in Cloud by Neural Net and Entropy Calculation"
Igor Trubin began his engineering career in 1979 as an IBM/370 systems engineer. He earned a Ph.D. in Robotics from St. Petersburg Technical University in 1986 and spent 12 years there as a professor teaching CAD/CAM and Robotics. He has published and presented more than 60 technical papers and conference presentations in robotics, artificial intelligence, IT performance, capacity management, anomaly detection, and FinOps. After moving to the U.S. in 1999, Igor worked at Capital One, IBM, and SunTrust Bank in senior engineering, architecture, and management roles. His 2002 CMG paper on exception detection received a Best Paper Award. He later developed Perfomalist.com, based on his original methods for anomaly, change-point, and trend detection, and created the online course “Performance Anomaly Detection.” At Capital One, he led development of cloud capacity-management and FinOps solutions, including the award-winning OptiCloud application. He has served on the CMG Board of Directors since 2015. Now semi-retired, Igor focuses on research, writing, and consulting. His current work expands his concept of the “Area of Normal Functioning” (ANF) from technical systems to human, orga
5 comments:
Igor, Excellent presentation and proposal using the most effective ML techniques! Congrats to CMG keeping these skills!
9017618D5C
Takipçi Satın Al
En İyi Ücretsiz Oyunlar
Dizi Önerileri
CAF075C2
Forum
Forum
Forum
Forum
Forum
Forum
Forum
Forum
Forum
A7C7F51E
Burdur
Elazığ
Gümüşhane
Siirt
Kırıkkale
Bolu
Yozgat
Niğde
Balıkesir
6FB39705
Eşme
Akçakoca
Samandağ
Sapanca
Körfez
Çarşamba
Kaş
Dikmen
Kınık
Post a Comment