BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20170418T171710Z UID:ed646bfb-90f2-432b-86c1-5564b3905bad DTSTART;TZID=America/Phoenix:20170426T105000 DTEND;TZID=America/Phoenix:20170426T113000 DESCRIPTION:Machine Learning is no longer just an academic study. Tools lik e Tensorflow have opened new doorways in the world of application developm ent. Learn about the current tools available and how easy it is to integra te them into your rails application. We'll start by looking at a real-worl d example currently being used in the wild and then delve into creating a sample application that utilizes machine learning. \n\n \n A passion for cooking\, programming\, and Japanese brought Ma tt to work at Cookpad\, an international recipe sharing website. As a memb er of the web team he works to bring together all the technologies they us e into the international rails application. Recent adventures has brought about an interest in Machine Learning and figuring out how to use it in or der to change the ways we create and share recipes.\n\nMatthew Mongeau\n \n \n A passion for cooking\ , programming\, and Japanese brought Matt to work at Cookpad\, an internat ional recipe sharing website. As a member of the web team he works to brin g together all the technologies they use into the international rails appl ication. Recent adventures has brought about an interest in Machine Learni ng and figuring out how to use it in order to change the ways we create an d share recipes. LOCATION:156 SUMMARY:Is it Food? An Introduction to Machine Learning (Machine Learning) END:VEVENT BEGIN:VEVENT DTSTAMP:20170418T171710Z UID:cdf6948e-d2e2-4220-9efa-7056992ccf92 DTSTART;TZID=America/Phoenix:20170426T114000 DTEND;TZID=America/Phoenix:20170426T122000 DESCRIPTION:What's a better way to understand machine learning than a pract ical example? And who hasn't watched the 1997 classic with Jack and Rose? In this talk we will first take a look at some real historical data of the event. Then we will use amazing Python libraries to live code several of the most well known algorithms. This will help us understand some fundamen tal concepts of how machine learning works. When we're done\, you should h ave a good mental framework to make sense of it in the modern world.\n\n \n Ju was born in China\, then as a kid moved t o Italy. He grew up and cofounded a consulting company in Turin. After som e time\, he decided to start a new adventure and moved to London\, where h e works at Erlang Solutions as an Elixir Engineer. He loves to solve hard problems and build amazing products. When he’s not doing that\, he⠀™s probably rock climbing.\n\nJu Liu\n \n \n Ju was born in China\, then as a kid moved to Italy. He grew up and cofounded a consulting company in Turin. After some time\, he decided to start a new adventure and moved to London\, where he works a t Erlang Solutions as an Elixir Engineer. He loves to solve hard problems and build amazing products. When he’s not doing that\, he’s prob ably rock climbing. LOCATION:156 SUMMARY:Predicting Titanic Survivors with Machine Learning (Machine Learnin g) END:VEVENT BEGIN:VEVENT DTSTAMP:20170418T171710Z UID:d2a13b50-c490-4372-839d-fde791fc945e DTSTART;TZID=America/Phoenix:20170426T135000 DTEND;TZID=America/Phoenix:20170426T143000 DESCRIPTION:Before programming\, before formal probability there was Bayes. He introduced the notion that multiple uncertain estimates which are rela ted could be combined to form a more certain estimate. It turns out that t his extremely simple idea has a profound impact on how we write programs a nd how we can think about life. The applications range from machine learni ng and robotics to determining cancer treatments. In this talk we'll take an in depth look at Bayses rule and how it can be applied to solve problem s in programming and beyond.\n\n \n Schneems w rites Ruby at Heroku\, maintains CodeTriage.com\, and co-organizes Keep Ru by Weird. He is in the top 50 Rails contributors and is an accidental main tainer of Sprockets. He writes such gems as Wicked\, and derailed_benchmar ks.\n\nRichard Schneeman\n \n \n Schneems writes Ruby at Heroku\, maintains CodeTriage.com\, and co-o rganizes Keep Ruby Weird. He is in the top 50 Rails contributors and is an accidental maintainer of Sprockets. He writes such gems as Wicked\, and d erailed_benchmarks. LOCATION:156 SUMMARY:Bayes is BAE (Machine Learning) END:VEVENT BEGIN:VEVENT DTSTAMP:20170418T171710Z UID:3d4a9e0f-7f7a-4a3a-aa41-c2b8e3c5e0ee DTSTART;TZID=America/Phoenix:20170426T144000 DTEND;TZID=America/Phoenix:20170426T152000 DESCRIPTION:Natural Language Processing is an interesting field of computin g. The way humans use language is nuanced and deeply context sensitive. Fo r example\, the word work can be both a noun and a verb. This talk will gi ve an introduction to the field of NLP using Ruby. There will be demonstr ations of how computers fail and succeed at human language. You'll leave t he presentation with an understanding of both the challenges and the possi bilities of NLP and some tools for getting started with it. \n\n \n Aja lives in Seattle where she is a Developer Advoca te at Google and a member of the Seattle Ruby Brigade. Her favorite langua ges are Ruby and Prolog. She also loves working with large piles of data. In her free time she enjoys skiing\, cooking\, knitting\, and long coding sessions on the beach.\n\nAja Hammerly\n \n \n Aja lives in Seattle where she is a Developer Advocate at Google and a member of the Seattle Ruby Brigade. Her favorite language s are Ruby and Prolog. She also loves working with large piles of data. In her free time she enjoys skiing\, cooking\, knitting\, and long coding se ssions on the beach. LOCATION:156 SUMMARY:Syntax Isn't Everything: NLP for Rubyists (Machine Learning) END:VEVENT END:VCALENDAR