Machine learning (ML) and deep learning (DL) content from the past 24 hours.
— Spark Summit East will meet in Boston February 7-9 2017.
— In The Next Platform, Nicole Hemsoth explains why Microsoft invests in FPGAs for compute-intensive applications like machine learning. Separately, Nicole investigates Intel’s strategy to integrate the deep learning assets it acquired when it bought Nervana earlier this year.
— Benedict Evans speculates about the impact of cheap and pervasive cameras combined with image recognition technology.
— The Economist claims that economists love fads and machine learning is the latest fashion. The article is self-debunking. The chart below shows gradual assimilation over thirty years, not Pavlovian fashion-following.
— In Harvard Business Review, Anastassia Fedyk explains how to tell if machine learning can solve your business problem.
— Tyler Lacoma argues, cryptically, that machine learning is more advanced than ever before, but it’s not Judgement Day yet. That’s a relief.
— A Quora reader requests advice for novice machine learning users who feel overwhelmed. Sebastian Raschka responds. My advice: change careers. Successful data scientists tend to feel energized by all of the resources available today.
— Adrian Sampson describes three common statistical mistakes and how to avoid them.
Methods and Techniques
— Here is the complete series of posts on Topic Modeling from the BigML blog. If you don’t know what Topic Modeling is, read the series.
— Bioinformatics maven Shirin Glander asks: can we predict flu deaths with machine learning and R? She proceeds to answer the question by demonstrating multiple ways to do so in a tour de force post, with graphics and code snippets.
— Serdar Yegualp explains why AWS standardized on MXNet for DL.
— Baidu releases “Long Utterance,” a set of Chinese language APIs for its speech recognition technologies.
— The Editorial Team at Inside Big Data gushes over IBM Watson Machine Learning because it is “built on Apache Spark.” In fact, IBM Watson Machine Learning is a rebranded managed service for SPSS Modeler.
— TechCrunch reports that Japan’s Ministry of Economy, Trade, and Industry plans to spend 20 billion yen to build a supercomputer capable of 130 petaflops. That’s a lot of yen and a lot of flops.
— NVIDIA Foundation awards $200K to the Translational Genomics Research Institute to perfect its software for the analysis of cancer cell genes.
— Nokia offers embedded machine learning to telcos for mobile customer experience analytics and customer care.
— In Business Insider, Lydia Ramsey describes five impactful innovations in radiology; machine learning drives two of the five.
Bottom Story of the Day
— In TechCrunch, Chris Nicholson argues that machine learning can fix America.