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FOUNDER OF BYOR - AI Using the BEST 2016

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FOUNDER OF BYOR - AI With all the BEST 2016

AI Using the Best could be the biggest online conference for data scientist, developers, tech teams and startups happening the 24th & 25th September 2016 providing you with 100 incredible speakers via a novel, online conference platform. Meet Aerin Kim, Data Scientist turned Founding father of startup BYOR  (Construct your Own Resume) speaking at AI With 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 for the webapp, it gives suggestions on the way to increase your resume regarding its wording or phrases.

Please show somewhat concerning your background before BYOR and just how did you end up in data?

I had been a NLP data scientist at the startup called Boxfish. Used to do a lot of Twitter text modeling there and had been fascinated daily through the level of information that may be gleaned all the text that individuals were generating. Because it was obviously a startup, we was building the product on your own over many iterations. That training reduced the problem later while i turned my idea in a product (BYOR).

What propelled that you push NLP parsing technology for Resumés?

My co-founder and I have been volunteering as resume reviewers and mentors for Columbia University since 2014. Yearly, we found there is a pattern for weak resumes and we found ourselves giving students precisely the same advice every year. We were treated to an opportunity for some automation on this resume reviewing process.

Also at school career centers, it’s difficult to get a one-on-one session with career advisors since the student-to-advisor ratio is hundreds to 1. We decided to create a tool that is employed by students to review their resume before meeting their career advisors, or alternatively.

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

How can you train the word embedding neural networks to get similarities and relations between phrases?

The key strategy for finding similarities and relations between two different phrases is converting the crooks to phrase vectors and after that seeking the distance between these vectors. There are several ways to calculate phrase vectors. The best way that one can try is usually to first train the phrase vectors and after that weight average those word vectors found in the phrases.

Exactly what do BYOR do when compared with other CV checkers?

Currently, there is no company that suggests result phrases over a specific sentence. Even AI companies with higher level of funding don’t open their platforms like us. Inviting individuals to upload just about any resume and provides them suggestions is often a challenging problem on many levels and taking it on takes a little bravery.

What traditional CV checkers do is simple keyword extraction or keyword counting to evaluate whether certain test is used or otherwise. They don’t comprehend the user’s resume line by line semantically.

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

Essentially the most exciting part is the place we improve the “phrase suggestion algorithm” day-to-day and reach your goals in generating phrases that make sense.

Also, prior to the startup, That i used to work with a huge bank. If you're an employee of a big company, your job description is very narrowly focused. But also in a startup, I can experiment with all the parts in the product. Many experts have exciting personally to date.

Also, it’s amazing to see many people contributing to BYOR voluntarily.

If it’s not a secret, which can be your favourite technological setup?   

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

To teach word vectors, we use code written in C.

What advice would you give to budding AI developers?

Should you be AI developer, Applied Math basics are essential for you. Invest a number of your time and efforts to go over Linear Algebra, Optimization, Probability that you learned during college.

Are you enthusiastic about speaking at AI Together with the Best?

Yes! I love that it’s priced under 100 bucks so that average person can attend. And it’s online!!! People/students shouldn’t require sponsors to wait such tech conferences. With all the Best line-up will be as good as being a $3000 conference.