Interesting PDF document featuring 15 data scientists (mostly co-founders of various start-ups or well known data science websites), with an average of 9 pages per interview.
Parham Aarabi: Visual Image Extraction - CEO of ModiFace & University of Toronto Professor Pete Warden: Object Recognition - Co-Founder & CTO of Jetpac Trey Causey: Data Science & Football - Founder of the spread, Data Scientist at zulily Ravi Parikh: Modernizing Web and iOS Analytics - Co-Founder of Heap Analytics (YC W13) Ryan Adams: Intelligent Probabilistic Systems - Leader of Harvard Intelligent Probabilistic Systems Group Kang Zhao: Machine Learning & Online Dating - Assistant Professor, Tippie College of Business, University of Iowa Dave Sullivan: Future of Neural Networks and MLaaS - Founder and CEO of Blackcloud BSG - company behind Ersatz Wolfgang van Loeper: Big Data & Agriculture - Founder & CEO of MySmartFarm Laura Hamilton: Predicting Hospital Readmissions - Founder & CEO of Additive Analytics Harlan Harris: Building a Data Science Community - Founder and President of Data Community DC Abe Gong: Using Data Science to Solve Human Problems - Data Scientist at Jawbone, DataScienceWeekly.orgK. Hensien & C. Turner: ML => Energy Efficiency - Senior Product Development at Optimum Energy, Data Scientist at The Data Guild Andrej Karpathy: Training DL Models in a Browser - Machine Learning PhD student at Stanford, Creator of ConvNetJS George Mohler: Predictive Policing - Chief Scientist at PredPol, Asst. Professor Mathematics & CS, Santa Clara University Carl Anderson: Data Science & Online Retail - Director of Data Science at Warby Parker
Caffe already powers academic research projects, startup prototypes, and even large-scale industrial applications in vision, speech, and multimedia. There is an active discussion and support community on Github.
Today the photograph has transformed again. From the old world of unprocessed rolls of C-41 sitting in a fridge 20 years ago to sharing photos on the 1.5” screen of a point and shoot camera 10 years back.
This code produces an infinite supply of digit images derived from the well known MNIST dataset using pseudo-random deformations and translations. This is a streamlined version of the code used for the experiments reported in (Loosli, Canu, Bottou, 2007). A subset of the examples generated by this code are known as MNIST8M.
I never got round to writing a tutorial on how to use word2vec in gensim. It s simple enough and the API docs are straightforward, but I know some people prefer more verbose formats. Let this post be a tutorial and a reference example.
The annual useR! international R User conference is the main meeting of the R user and developer community. In 2014, the conference will be held at the campus of the University of California in Los Angeles (UCLA).