Ride a bike, machine learn the path, have a beer, see Portland, or come to find the artificial intelligence you’ve been looking for on our ML4ALL Ride! Ok, fancy word play aside, we’ll be having a ride the Sunday of the conference in Portland, and I’ve put together the route below. I’ll have more information about the ride real soon and look forward to others joining me for the slow roll. Stay tuned and I’ll have a LOT more details, but now, meet two more of our upcoming speakers; Igor and Carol!
Teach Machine To Teach: Personal Tutor For Language Learners
Have you ever learned a foreign language? If yes, you’ve probably written translations of new words on pieces of paper or saved them in digital text documents. What happened thereafter? I guess you would rarely read these vocabulary lists more than a few times, if ever, but you’d still continue making “new words” lists anyway. Writing down and forgetting, making new lists and forgetting again.
How can we help ourselves learn faster and significantly reduce number of words immediately disappearing from our memory? What if you had someone who would remember all your translation history and prepare for you a list of recommended articles and videos based on words you translated? Let’s explore how Machine Learning can be applied to help simplify the process of learning a new language! In this talk, I will be glad to show you how to implement this kind of recommendation system using Machine Learning!”
Meet Igor Dziuba (@dziubaigor) is a founder of Store Translate, lead Big Data Engineer at EPAM Systems with Scala/Java as primary programming languages.
TBD
Alright, so the talk Carol (@Robot_MD) is going to provide, so far, is top secret! But let me introduce Carol and her work!
Carol is an entrepreneur, roboticist, and executive, currently delving into ideas around AI, healthcare, and diversity. She’s also a cofounder and board member of drive.ai, an artificial intelligence self-driving vehicle startup.
She’s also an NSF Graduate Research Fellow, did her graduate academic research and worked as an instructor of intersession courses at Johns Hopkins University. Not just that, she’s also got eight technical patents, is the author of a dozen plus papers on scientific conference proceedings, refereed journals, and conferences. Needless to say, Carol has a long long long list of awesome accomplishments and cool projects, which you can check out at http://creiley.com.
I’m super stoked to find out what, and see her present at ML4ALL! To checkout ML4ALL and get your tickets navigate over to ML4ALL here!
- Manuel -> Barriers To Accelerating The Training Of Artificial Neural Networks – A Systemic Perspective
- Ashutosh -> Conducting a Data Science Contest in Your Organization
- Poul -> From Zero to Machine Learning for Everyone
- Anna -> Your First NLP Machine Learning Project: Perks and Pitfalls of Unstructured Data
- Kaleo Ha’o -> Jump or Not to Jump: Solving Flappy Bird with Deep Reinforcement Learning
- Mary & Robert -> Eliminating Machine Bias & Getting from Machine Learning Outputs to Decisions… timely things!
- Kirsten & Rich -> Now, Kirsten Westeinde & Rich Jolly
- Jon & Amy -> Say Hello to Jon and Amy @ML4ALL!
- Igor & Carol -> More @ML4ALL Intros: Meet Igor & Carol! Also, the bike ride map!
- Clair & Ricky -> @ML4ALL Meet Clair J. Sullivan & Ricky Hennessy
- Paige & Suz -> ML4ALL Speakers – Meet Paige & Suz
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