Computer vision and Machine learning developer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AudioNet-V1
February 10, 2018 – February 11, 2018
1D CNN based classifier for Speech Commands Dataset
View ProjectNIST-Digits-using-Keras
March 12, 2017 – March 12, 2017
Sample CNN training for NIST digits dataset using Keras
View ProjectNIST-Handwritten-Alphabets-Lowercase
February 11, 2017 – March 11, 2017
Googlenet trained Caffemodel for Alphabets (lower case) from NIST dataset
View ProjectNIST-Handwritten-Alphabets-Caps
February 3, 2017 – March 11, 2017
Googlenet trained Caffemodel for Alphabets (Caps) from NIST dataset
View ProjectNIST-Handwritten-digits
January 31, 2017 – March 11, 2017
Googlenet trained Caffemodel for digits from NIST dataset
View ProjectCultural Fit Analysis
The candidate's projects are primarily focused on personal machine learning experiments, indicating a self-driven learning approach. However, the lack of team-based projects or diverse technology stacks limits the assessment of broader cultural fit and collaboration potential. The projects align with a technical role, but the specific target role of 'Software Engineer' is broad, and the projects lean heavily towards ML research rather than general software engineering practices.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback are available.