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Rajesh S Korde

from Sammamish, WA
Age ~49

Rajesh Korde Phones & Addresses

  • 2921 229Th Pl NE, Sammamish, WA 98074 (989) 333-6731
  • Redmond, WA
  • Seattle, WA
  • Lansing, MI
  • 4640 Hagadorn Rd, East Lansing, MI 48823 (517) 333-6731
  • 4632 Hagadorn Rd, East Lansing, MI 48823
  • Kiona, WA

Work

Company: Microsoft Mar 2014 Position: Principal data scientist manager

Skills

Data Science • Statistics • Design of Experiments • A/B Testing • Predictive Modeling • Survival Analysis • Algorithms • Business Analysis • Management • Software Engineering • Agile Methodologies • Software Development • Software Design • C++ • C# • Test Automation

Languages

English • Hindi • Marathi • Bengali

Ranks

Certificate: License Rcsdze7Qqacv

Industries

Computer Software

Resumes

Resumes

Rajesh Korde Photo 1

Principal Data Scientist Manager

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Location:
2921 229Th Ave, Sammamish, WA 98074
Industry:
Computer Software
Work:
Microsoft
Principal Data Scientist Manager
Skills:
Data Science
Statistics
Design of Experiments
A/B Testing
Predictive Modeling
Survival Analysis
Algorithms
Business Analysis
Management
Software Engineering
Agile Methodologies
Software Development
Software Design
C++
C#
Test Automation
Languages:
English
Hindi
Marathi
Bengali
Certifications:
License Rcsdze7Qqacv
License 8S7Rvlvdqvbz
Data Science Specialization
Bayesian Statistics
Coursera Verified Certificates, License Rcsdze7Qqacv
Coursera Course Certificates, License 8S7Rvlvdqvbz

Publications

Us Patents

Software Categorization Based On Knowledge Graph And Machine Learning Techniques

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US Patent:
20210350252, Nov 11, 2021
Filed:
May 7, 2020
Appl. No.:
16/869347
Inventors:
- Redmond WA, US
Ahsanul Haque - Bellevue WA, US
Rajesh Shashikant Korde - Sammamish WA, US
Minglei Huang - Bothell WA, US
Rui Zhu - Sammamish WA, US
International Classification:
G06N 5/04
G06N 20/00
Abstract:
Methods and systems are provided for determining the category of a software application utilizing machine learning (ML) and knowledge graph techniques, and for controlling access to the application by a user based on the category and configured time restrictions for the user. The system includes a feature set extractor and a category predictor with a trained ML model. The trained ML model generates the category of the application based on a feature(s) of the application. The generated category is indicated in a data structure. An access request handler receives a request related to access to the application from a user device. A category determiner determines the category of the application from the data structure. A time usage manager determines an available time usage for the category and the specified user. The access arbiter responds to the request from the user device with the available time usage.
Rajesh S Korde from Sammamish, WA, age ~49 Get Report