Raising capital for a shiny new start-up company is a daunting task what with shoring up interest by funding sources like Angels and VCs, producing a compelling “pitch deck,” and stacking your management team with the right people. But the big elephant in the room is always – how much to raise? Entrepreneur Jamie Davidson recently put some science (data science that is) behind this very important question.
As social media becomes increasingly important as a data source for the purposes of machine learning, finding a brand new method for analyzing the Twitter microblogging platform is very compelling. Tauid Zaman, assistant professor at MIT’s Sloan School of Management, developed a probabilistic model for the spread of an individual tweet in the twitterverse.
Enterprise Strategy Group (ESG), a leading analyst firm, recently performed a hands-on evaluation of Hadapt Adaptive Analytical Platform for big data.
Information visualization is an increasingly important element of big data as it is the technology best able to convey the message emanating from the data. Here is a nice paper “Infovis and Statistical Graphics: Different Goals, Different Looks” (pdf) by Andrew Gelman (Professor of Statistics at Columbia University) and Antony Unwin that discusses the topic of information visualization.
I’d like to acquaint you with a tremendous resource for keeping current with the latest research in the field of machine learning. Informally known as the pre-print server, arXix.org is the global repository for the fields of Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance and Statistics.
As 2013 draws to a close, a number of year-end surveys are coming out to assess the progress in our industry. I enjoy going through these results to get a pulse of big data and how it’s being received in the business community. Here is one valuable survey published annually for free: Rexer Analytics 6th Data Miner Survey for 2013.
On Tuesday Facebook announced it hired machine learning pioneer Yann LeCun to run its newly created artificial intelligence lab. Scooping up one of the biggest names in the field is a major move for the company, but it’s not a surprising one. If anything, Facebook is late to enter to the data science arms race that’s underway in Silicon Valley and the country as a whole.