Machine learning Quotes

“Machine learning is the science of getting computers to learn without being explicitly programmed.”

“Machine learning is the science of getting computers to learn without being explicitly programmed.”

“Due to the various pragmatic obstacles, it is rare for a mission-critical analysis to be done in the “fully Bayesian” manner, i.e., without the use of tried-and-true frequentist tools at the various stages. Philosophy and beauty aside, the reliability and efficiency of the underlying computations required by the Bayesian framework are the main practical issues. A central technical issue at the heart of this is that it is much easier to do optimization (reliably and efficiently) in high dimensions than it is to do integration in high dimensions. Thus the workhorse machine learning methods, while there are ongoing efforts to adapt them to Bayesian framework, are almost all rooted in frequentist methods. A work-around is to perform MAP inference, which is optimization based.Most users of Bayesian estimation methods, in practice, are likely to use a mix of Bayesian and frequentist tools. The reverse is also true—frequentist data analysts, even if they stay formally within the frequentist framework, are often influenced by “Bayesian thinking,” referring to “priors” and “posteriors.” The most advisable position is probably to know both paradigms well, in order to make informed judgments about which tools to apply in which situations.”

“Artificial intelligence is one of 50 things that Watson does. There is also machine learning, text-to-speech, speech-to-text, and different analytical engines - they're like little Lego bricks. You can put intelligence in any product or any process you have.”

“Cyber hygiene, patching vulnerabilities, security by design, threat hunting and machine learning based artificial intelligence are mandatory prerequisites for cyber defense against the next generation threat landscape.”

“When you apply computer science and machine learning to areas that haven't had any innovation in 50 years, you can make rapid advances that seem really incredible.”

“One of the things we did at PayPal was collaborative filtering and machine learning: looking at patterns of human behavior. We used it there to predict when people would try to cheat the system to get money. But you can predict pretty much any behavior with a certain amount of accuracy.”