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M Tech student at National Institute of Technology, Surathkal, Mangalore, Karnataka.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Exhaustive-evaluation-of-Cautious-Slow-Start-CSS-in-WiFi-environments.
March 11, 2018 – April 11, 2018
Exhaustive-evaluation-of-Cautious-Slow-Start-CSS-in-WiFi-environments. — GitHub repository
View ProjectHeart_Disease_Prediction_using_Machine_Learning
February 24, 2018 – February 24, 2018
Heart Disease Prediction using Machine Learning
View ProjectImplementation-of-Balanced-RED-in-ns-3
February 23, 2018 – February 24, 2018
Implementation of Balanced RED AQM in ns-3
View ProjectDiabetes_Prediction_using_Machine_Learning
November 20, 2017 – November 20, 2017
Diabetes_Prediction_using_Machine_Learning — GitHub repository
View ProjectHigh-Performance-Computing-frequent-item-set-using-CUDA
October 17, 2017 – November 30, 2017
This is a project of subject CS701 High Performance Computing of Mtech at NITK. It calculates fequent item set using CUDA
View ProjectImplementation-of-Non-Linear-RED-in-Linux-Kernel
September 12, 2017 – November 25, 2017
Implementation of Non Linear RED AQM in Linux Kernel
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards academic and research-oriented tasks, particularly in networking and machine learning. The diversity of technologies (Python, C++, Shell, Go, Ruby, HCL, Matlab, Perl, Cuda, Assembly, Objective C, Makefile) indicates a broad technical curiosity. However, the projects are predominantly personal and lack explicit team collaboration or real-world business impact, which might be a consideration for cultural fit in a fast-paced industry setting. The target role is 'Data Scientist', and while there are relevant ML projects, the breadth of other technologies suggests a wider interest beyond pure data science.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.