Almost a dozen almost-truisms about Data that almost everyone should consider carefully as they embark on a journey into Data Science. There are a number preconceptions about working with data at scale where the realities beg to differ. This talk estimates that number to be at least eleven, through probably much larger. Let's consider some of the less-intuitive directions in which this field is heading, along with likely consequences and corollaries -- especially for those who are just now beginning to study about the technologies, the processes, and the people involved.
•6:00 pm - 6:30 pm: Guests Welcome
• 6:30 pm - 7:30 pm: Networking
• 7:30 pm - 8 pm: Kenny Daniel's talk
• 8 pm - 9 pm: Paco Nathan's talk
Meet The Speakers:
Paco Nathan, is a "player/coach" who has led innovative Data teams building large-scale apps for several years. He has expertise in distributed systems, machine learning, functional programming, and cloud computing, and is an O'Reilly author, Apache Spark open source evangelist with Databricks, and an advisor for Amplify Partners and GalvanizeU. He received his BS Math Sci and MS Comp Sci degrees from Stanford University, and has 30+ years technology industry experience ranging from Bell Labs to early-stage start-ups. .
Kenny Daniel is CTO and founder of Algorithmia. A dual-major in Math and CS at Carnegie Mellon University, he pursued doctoral studies in Ai at USC before the startup bug bit him. Algorithmia is building a community around state-of-the-art algorithm development, where users can create, share and build on other algorithms.