Founding father of BYOR - AI With all the BEST 2016
AI With The Best is the biggest online conference for data scientist, developers, tech teams and startups happening the 24th & 25th September 2016 bringing you 100 incredible speakers by having a novel, online conference platform. Meet Aerin Kim, Data Scientist turned Founding father 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. Each time a user uploads her resume around the webapp, it offers suggestions on how to improve your resume regarding its wording or phrases.
Please show a lttle bit relating to your background just before BYOR and just how did you enter data?
I was a NLP data scientist in a startup called Boxfish. Used to do lots of Twitter text modeling there together been fascinated daily by the quantity of information that could be gleaned from all of the writing that folks were generating. As it was a startup, all of us was building the product from scratch over many iterations. That training reduced the problem later after i turned my idea in to a product (BYOR).
What propelled you to definitely push NLP parsing technology for Resumés?
My co-founder and I are already volunteering as resume reviewers and mentors for Columbia University since 2014. Every year, we found there is a pattern for weak resumes and we found ourselves giving students the identical advice every single year. We had an opportunity for some automation in this resume reviewing process.
Also at college career centers, it’s challenging a one-on-one session with career advisors because the student-to-advisor ratio is hundreds to a single. We thought we would produce a tool that could be employed by students to check their resume prior to meeting their career advisors, or as an alternative.
The BYOR project started as the class problem for the CS 224d (Dr. Richard Socher) at Stanford. Rohit and i also took that class online.
How will you train the phrase embedding neural networks to discover similarities and relations between phrases?
The key approach to finding similarities and relations between two different phrases is converting the crooks to phrase vectors and then finding the distance between these vectors. There are many different solutions to calculate phrase vectors. The easiest way that anyone can try is always to first train the term vectors and after that weight average those word vectors used in the phrases.
Exactly what can BYOR do compared to other CV checkers?
Currently, there is no company that suggests result phrases with a specific sentence. Even AI companies with good volume of funding don’t open their platforms like us. Inviting website visitors to upload any type of resume and present them suggestions is often a challenging problem on many levels and taking it on requires a little bravery.
What traditional CV checkers do is straightforward keyword extraction or keyword counting to test whether certain test is used or otherwise not. They don’t view the user’s resume line by line semantically.
What’s been the most exciting portion of your startup adventure?
The most exciting part happens when we increase the “phrase suggestion algorithm” everyday and achieve generating phrases that make sense.
Also, prior to the startup, That i used to work with a major bank. An advanced employee of a big company, your career description is incredibly narrowly focused. However in a startup, I'm able to experiment with every aspect from the product. It is often extreme fun for me thus far.
Also, it’s amazing to view a lot of people leading to BYOR voluntarily.
If it’s a well known fact, 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 train word vectors, we use code written in C.
What advice would you give to budding AI developers?
In case you are AI developer, Applied Math basics are essential for you. Invest a number of your time go over Linear Algebra, Optimization, Probability that you simply learned during college.
Have you been excited about speaking at AI Using 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 is as good as being a $3000 conference.