Founding father of BYOR - AI With all the BEST 2016
AI Together with the Best may 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 by way of a novel, online conference platform. Meet Aerin Kim, Data Scientist turned Founder of startup BYOR (Construct 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 a superior suggestions on the way to enhance your resume regarding its wording or phrases.
Please inform us a bit about your background before BYOR and the way do you enter into data?
I became a NLP data scientist at the startup called Boxfish. I did a great deal of Twitter text modeling there along been fascinated each day with the level of information that could be gleaned from all the text that individuals were generating. As it would have been a startup, all of us was building the product or service from scratch over many iterations. That training helped me later while i turned my idea right into a product (BYOR).
What propelled one to push NLP parsing technology for Resumés?
My co-founder and I happen to be volunteering as resume reviewers and mentors for Columbia University since 2014. Each year, we found there's a pattern for weak resumes and that we found ourselves giving students the same advice every single year. We saw a way for some automation with this resume reviewing process.
Also in school 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 develop a tool that could be utilized by students to review their resume before meeting their career advisors, or alternatively.
The BYOR project started because the class work for the CS 224d (Dr. Richard Socher) at Stanford. Rohit i took that class online.
How will you train the term embedding neural networks to discover similarities and relations between phrases?
The primary strategy for finding similarities and relations between two different phrases is converting them to phrase vectors and then locating the distance between these vectors. There are numerous ways to calculate phrase vectors. The best way that anyone can try is usually to first train the term vectors after which weight average those word vectors found in the phrases.
Exactly what can BYOR do in comparison to other CV checkers?
Currently, there is no company that suggests result phrases with a specific sentence. Even AI companies with higher level of funding don’t open their platforms like us. Inviting people to upload just about any resume and provide them suggestions is often a challenging problem on many levels and taking it on uses a little bravery.
What traditional CV checkers do is straightforward keyword extraction or keyword counting to check whether certain test is used or not. They don’t view the user’s resume line by line semantically.
What’s been essentially the most exciting section of your startup adventure?
Essentially the most exciting part is the place we increase the “phrase suggestion algorithm” day by day and achieve generating phrases that make sense.
Also, ahead of the startup, I did previously help a huge bank. An advanced employee of a giant company, your career description is incredibly narrowly focused. But also in a startup, I could try out all parts in the product. It's been very exciting for me personally thus far.
Also, it’s amazing to view many people contributing to BYOR voluntarily.
If it’s a well known fact, which can be your favourite technological setup?
It’s not a secret. We use python django for web. All NLP/deep learning code is presented in python.
To practice word vectors, we use code designed in C.
What advice can you give budding AI developers?
If you are AI developer, Applied Math basics are essential for you. Invest several of your time and energy to go over Linear Algebra, Optimization, Probability which you learned during college.
Are you looking forward to speaking at AI With all 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 internet!!! People/students shouldn’t must have sponsors to go to such tech conferences. Together with the Best line-up is really as good as a $3000 conference.