The talk below, “Topological Data Analysis for the Working Data Scientist” was presented at the SF Data Mining meetup group. Speaker Anthony Bak begins with a short review of the Mapper algorithm and discuss how to think about problems in the topological framework.
In this short presentation, Dr. Andrew Ng (world renowned deep learning luminary, Chief Scientist of Baidu; Chairman and Co-Founder of Coursera; Stanford CS faculty) talks about what’s going on with deep learning and how it is rapidly changing the problem domains that can be addressed with machine learning. In particular, Ng announces a deep learning […]
Jeff Dean of Google presented this talk at BayLearn 2015. “In this talk, I’ll highlight some of the lessons we have learned in using our first-generation distributed training system and discuss some of the design choices in our second-generation system. I’ll then discuss ways in which we have applied this work to a variety of problems in Google’s products, usually in close collaboration with other teams.”
In this special guest feature for our Data Science 101 channel, Smita Adhikary of Big Data Analytics Hires highlights how data scientists sometimes tend to get bogged down in the “how” of a problem rather than the “why” of it, and end up delivering highly predictive, yet essentially meaningless models for the business.
In this special guest feature for our Data Science 101 channel, Smita Adhikary of Big Data Analytics Hires shares her thoughts about how the data science community has changed over the years – many useful tips for those just entering the field. Smita is a Managing Consultant at Big Data Analytics Hires – a talent search and recruiting firm focused primarily on Data Science and Decision Science professionals.