“This list of 500+ was started in 2012, updated in 2014 and also very recently according to the author. It was compiled by 101.datascience.community, and broken down by degree (master / bachelor / certificate / doctorate) and location (online / on-site.)” – Source Data Science Central Read More
In this episode of the O’Reilly Data Show, O’Reilly’s online managing editor Jenn Webb speaks with Natalino Busa on the topic of predictive analytics, the challenges of feature engineering, and a new class of techniques that is enabling features to emerge from patterns within the data.
They also discuss the relationship between predictive techniques and high-quality microservices, and how machine learning is being used to improve financial services. Listen to Podcast
In this Video by Ryan Compton, Head of Data Science at Clarifai, talks about using convolutional neural networks to deal with the problem of nudity detection. Watch Video
IN THIS FOURTH EDITION of the O’Reilly Data Science Salary Survey. They analyzed input from 983 respondents working in the data space, across a variety of industries— representing 45 countries and 45 US states.
Through the results of their 64-question survey, They’ve explored which tools data scientists, analysts, and engineers use, which tasks they engage in, and of course—how much they make. READ MORE
In this video, Tyler Akida presents a whirlwind tour of the evolution of massive-scale data processing at Google, from the original MapReduce paradigm to the high-level pipelines of Flume to the streaming approach of MillWheel to the portable, unified streaming/batch model of Google Cloud Dataflow and Apache Beam (incubating).
Tyler also highlights similarities and differences with related open source systems such as Flink, Spark, Storm, and Gearpump, calling out ways in which they’re converging on and diverging from the Beam model and what that means when running Beam pipelines on their respective runners. Watch Video