AI With The Best may be the biggest online conference for data scientist, developers, tech teams and startups happening the 24th & 25th September 2016 presenting to you 100 incredible speakers via a novel, online conference platform. Meet Aerin Kim, Data Scientist turned Founder of startup BYOR (Create 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. Every time a user uploads her resume for the webapp, it offers suggestions regarding how to enhance your resume regarding its wording or phrases.

Please inform us a little concerning your background before BYOR and just how do you enter into data?

I used to be a NLP data scientist in a startup called Boxfish. I did so a lot of Twitter text modeling there along been fascinated each day through the level of information that may be gleaned from all of the written text that individuals were generating. As it was obviously a startup, our team was building the product or service over completely from scratch over many iterations. That training taught me to be later after i turned my idea right into a product (BYOR).

What propelled one to push NLP parsing technology for Resum�s?

My co-founder i have already been volunteering as resume reviewers and mentors for Columbia University since 2014. Annually, we found there's a pattern for weak resumes and we found ourselves giving students the same advice every single year. We were treated to a way for some automation in this resume reviewing process.

Also at college career centers, it�s challenging a one-on-one session with career advisors since the student-to-advisor ratio is hundreds to a single. We thought we would produce a tool that may be utilised by students to check their resume prior to meeting their career advisors, or as an alternative.

The BYOR project started as the class task for the CS 224d (Dr. Richard Socher) at Stanford. Rohit and i also took that class online.

How do you train the phrase embedding neural networks to discover similarities and relations between phrases?

The main approach to finding similarities and relations between two different phrases is converting them to phrase vectors and after that finding the distance between these vectors. There are many different approaches to calculate phrase vectors. The most effective way that one can try is to first train the saying vectors then weight average those word vectors found in the phrases.

Exactly what can BYOR do in comparison with other CV checkers?

Currently, there's no company that implies result phrases on the specific sentence. Even AI companies with good quantity of funding don�t open their platforms like us. Inviting website visitors to upload any type of resume and present them suggestions is really a challenging problem on many levels and taking it on uses a little bravery.

What traditional CV checkers do is easy keyword extraction or keyword counting to check on whether certain words are used or otherwise not. They don�t understand the user�s resume line by line semantically.

What�s been the most exciting part of your startup adventure?

Probably the most exciting part occurs when we increase the �phrase suggestion algorithm� day by day and achieve generating phrases which make sense.

Also, before the startup, I used to benefit a major bank. If you are an employee of a big company, your work description is extremely narrowly focused. But in a startup, I will test out all the parts of the product. It has been very exciting for me personally thus far.

Also, it�s amazing to view many people leading to BYOR voluntarily.

If it�s a well known fact, that is your favourite technological setup?

It�s a well known fact. We use python django for web. All NLP/deep learning code is constructed in python.

To train word vectors, we use code developed in C.

What advice do you give budding AI developers?

If you are AI developer, Applied Math basics are essential in your case. Invest a few of your time and energy to go over Linear Algebra, Optimization, Probability that you learned during college.

Are you pumped up about speaking at AI Together with the Best?

Yes! I like that it�s priced under 100 bucks to ensure that average man or woman can attend. And it�s on the net!!! People/students shouldn�t must have sponsors to visit such tech conferences. With all the Best line-up is as good as a $3000 conference.

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