Inspiration
The problems faced by recruiters in resume sorting/selection and ranking
What it does
It generates a sorted list of candidates according to needs of recruiters
How we built it
Using Python, Django, MongoDB and Microsoft Azure
Challenges we ran into
Understanding and accommodating the needs of recruiters and students
Accomplishments that we're proud of
Gathering of recruiter data which helped in the efficiency of our algorithm
What we learned
Complexity and differences in different recruiters
What's next for Umadko Review-based student sort/ranking for recruiter
A solution which could use Machine Learning to review and give best candidates with maximum need satisfaction
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