Category Archives: Machine Learning
Python, Java, and R are Most Popular Machine Learning Programming Languages
Source: Jean Francois Puget Data based on job descriptions on indeed.com
Posted in Machine Learning
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Statistics and Machine Learning
The image above is taken from a data mining primer course SAS offered in 1998. Aatash Shah, CEO of Edvancer Eduventures, in KDnuggets: Machine learning requires no prior assumptions about the underlying relationships between the variables. You just have to throw … Continue reading
The Role of Data in Statistical Modeling and Machine Learning
Oliver Schabenberger, EVP and CTO, SAS, on The difference between Statistical Modeling and Machine Learning: We can… distinguish statistical modeling, classical machine learning and modern machine learning by the role of the data. In statistical modeling, the data guide us to … Continue reading
Who needs economists when ‘the data speak for themselves’?
The Economist: Machine learning is still new enough for the backlash to be largely restricted to academic eye-rolling. But some familiar themes are emerging in this latest craze. In principle, these new techniques should protect economists from their own sloppy … Continue reading
Posted in Big Data Analytics, Machine Learning
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O’Reilly AI Conference: 12 Observations About Artificial Intelligence
At the inaugural O’Reilly AI conference, 66 artificial intelligence practitioners and researchers from 39 organizations presented the current state-of-AI: From chatbots and deep learning to self-driving cars and emotion recognition to automating jobs and obstacles to AI progress to saving … Continue reading
Posted in AI, Machine Learning
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3 Takes on Debugging Machine Learning
S. Zayd Enam: The difficulty is that machine learning is a fundamentally hard debugging problem. Debugging for machine learning happens in two cases: 1) your algorithm doesn’t work or 2) your algorithm doesn’t work well enough. What is unique about … Continue reading
Posted in AI, Machine Learning
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Current Capabilities of Artificial Intelligence (AI)
Andrew Ng: Surprisingly, despite AI’s breadth of impact, the types of it being deployed are still extremely limited. Almost all of AI’s recent progress is through one type, in which some input data (A) is used to quickly generate some simple response (B)… … Continue reading
Machine Learning and AI Market Landscape, 2016
Shivon Zilis and James Cham, O’Reilly: For the first time, a “one stop shop” of the machine intelligence stack is coming into view—even if it’s a year or two off from being neatly formalized. The maturing of that stack might explain why … Continue reading
Visually Linking AI, Machine Learning, Deep Learning, Big Data and Data Science
Source: Battle of the Data Science Venn Diagrams HT: KDnuggets What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning? Over the past few years AI has exploded, and especially since 2015. Much of that has to do with the … Continue reading