Founding father of BYOR - AI Using the BEST 2016
AI With The Best could be the biggest online conference for data scientist, developers, tech teams and startups happening the 24th & 25th September 2016 bringing you 100 incredible speakers through a novel, online conference platform. Meet Aerin Kim, Data Scientist turned Founder of startup BYOR (Create 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 around the webapp, it gives suggestions on the way to increase your resume regarding its wording or phrases.
Please show a little about your background ahead of BYOR and how have you enter into data?
I had been a NLP data scientist at a startup called Boxfish. I did plenty of Twitter text modeling there together been fascinated every day by the volume of information that could be gleaned coming from all the text that individuals were generating. As it was obviously a startup, we was building the item on your own over many iterations. That training reduced the problem later while i turned my idea into a product (BYOR).
What propelled that you push NLP parsing technology for Resumés?
My co-founder and i also have been volunteering as resume reviewers and mentors for Columbia University since 2014. Each year, we found you will find there's pattern for weak resumes and now we found ourselves giving students the identical advice every single year. We saw an opportunity for some automation within 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 one. We decided to build a tool that could be employed by students to analyze their resume ahead of meeting their career advisors, or as a substitute.
The BYOR project started because class project for the CS 224d (Dr. Richard Socher) at Stanford. Rohit and that i took that class online.
How will you train the word embedding neural networks to find similarities and relations between phrases?
The principle approach to finding similarities and relations between two different phrases is converting the crooks to phrase vectors and after that finding the distance between these vectors. There are many different ways to calculate phrase vectors. The best way that anyone can try is usually to first train the saying vectors then weight average those word vectors used in the phrases.
What can BYOR do in comparison to other CV checkers?
Currently, there is no company that means result phrases with a specific sentence. Even AI companies with higher volume of funding don’t open their platforms like us. Inviting website visitors to upload just about any resume and give them suggestions can be a challenging problem on many levels and taking it on takes a little bravery.
What traditional CV checkers do is straightforward keyword extraction or keyword counting to check on whether certain words are used you aren't. They don’t understand the user’s resume line by line semantically.
What’s been one of the most exciting section of your startup adventure?
The most exciting part is when we enhance the “phrase suggestion algorithm” day-to-day and succeed in generating phrases that will make sense.
Also, prior to the startup, That i used to work with a large bank. If you are a employee of a big company, your work description is quite narrowly focused. But also in a startup, I could try out all the parts of the product. It's been exciting personally so far.
Also, it’s amazing to view a lot of people adding to BYOR voluntarily.
If it’s not a secret, which can be 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 train word vectors, we use code developed in C.
What advice could you share with budding AI developers?
In case you are AI developer, Applied Math basics are essential for you. Invest some of your time and effort to debate Linear Algebra, Optimization, Probability that you simply learned during college.
Have you been enthusiastic about speaking at AI With The Best?
Yes! I love that it’s priced under 100 bucks in order that average person can attend. And it’s online!!! People/students shouldn’t have to have sponsors to visit such tech conferences. Together with the Best line-up can be as good being a $3000 conference.