FOUNDER OF BYOR - AI With all the BEST 2016
AI With all the Best may be the biggest online conference for data scientist, developers, tech teams and startups happening the 24th & 25th September 2016 giving you 100 incredible speakers via a novel, online conference platform. Meet Aerin Kim, Data Scientist turned Founder of startup BYOR (Build Your Own Resume) speaking at AI With all the Best, online tech conference about her Phrase2Vec technology. Aerin is building an AI-based resume helper using NLP parsing. When a user uploads her resume on the webapp, it offers suggestions on the way to boost your resume regarding its wording or phrases.
Please inform us somewhat regarding your background ahead of BYOR and just how would you get into data?
I became a NLP data scientist with a startup called Boxfish. I did so plenty of Twitter text modeling there together been fascinated every day with the volume of information that is gleaned all the words that people were generating. Since it was obviously a startup, we was building the merchandise over completely from scratch over many iterations. That training helped me later when I turned my idea right into a product (BYOR).
What propelled you to push NLP parsing technology for Resumés?
My co-founder and i also happen to be volunteering as resume reviewers and mentors for Columbia University since 2014. Annually, we found there exists a pattern for weak resumes and we found ourselves giving students the same advice year after year. We got a way for some automation with this resume reviewing process.
Also at college career centers, it’s difficult to get a one-on-one session with career advisors as the student-to-advisor ratio is hundreds to at least one. We thought we would produce a tool that might be employed by students to examine their resume just before meeting their career advisors, or alternatively.
The BYOR project started because class project for the CS 224d (Dr. Richard Socher) at Stanford. Rohit and I took that class online.
How do you train the saying embedding neural networks to locate similarities and relations between phrases?
The main strategy for finding similarities and relations between two different phrases is converting these to phrase vectors after which finding the distance between these vectors. There are several approaches to calculate phrase vectors. The simplest way that you can try is to first train the word vectors and after that weight average those word vectors employed in the phrases.
Exactly what can BYOR do when compared with other CV checkers?
Currently, there isn't any company that suggests result phrases on the specific sentence. Even AI companies with good level of funding don’t open their platforms like us. Inviting website visitors to upload virtually any resume and provides them suggestions is really a challenging problem on many levels and taking it on takes a little bravery.
What traditional CV checkers do is not hard keyword extraction or keyword counting to check whether certain words are used you aren't. They don’t comprehend the user’s resume line by line semantically.
What’s been probably the most exciting part of your startup adventure?
Essentially the most exciting part is when we increase the “phrase suggestion algorithm” day-to-day and reach your goals in generating phrases that will make sense.
Also, before the startup, That i used to work for a huge bank. If you are an employee of a giant company, your job description is extremely narrowly focused. But in a startup, I can research every part in the product. Many experts have extreme fun personally up to now.
Also, it’s amazing to see many individuals causing BYOR voluntarily.
If it’s a well known fact, that's your favourite technological setup?
It’s not a secret. We use python django for web. All NLP/deep learning code is written in python.
To practice word vectors, we use code developed in C.
What advice would you give budding AI developers?
If you are AI developer, Applied Math basics are necessary for you personally. Invest a few of your time to debate Linear Algebra, Optimization, Probability which you learned during college.
Do you think you're excited about speaking at AI Together with the Best?
Yes! I like that it’s priced under 100 bucks so that average man or woman can attend. And it’s online!!! People/students shouldn’t require sponsors to visit such tech conferences. With all the Best line-up will be as good being a $3000 conference.