Feature engineering headache disappears with deep learning - TotalCIO

One of the biggest differences between machine learning and deep learning is the effort that goes into making the algorithms work. With machine learning, data scientists have to perform a task called feature engineering. "People get the incoming data, and they prepare it, and they clean it, and they maybe manipulate it in a way that's going to give them the relevant information," said Edd Wilder-James, former vice president of technology strategy at Silicon Valley Data Science and now an open source strategist at Google's TensorFlow, during a presentation at the Strata Data Conference. Looking to establish accountability across disparate project teams? Trying to automate processes or allow for lean methodology support?