To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

Four pillars of ML Integrity in Production Systems Production ML systems have many moving parts. At the center is the Model, the trained AI algorithm that is used to generate predictions.

Recently, Shaila Niazi, a third-year doctoral student in Çamsari’s lab, achieved a significant breakthrough in that effort, becoming the first to use probabilistic hardware to train a deep generative ...

Curate training datasets more easily based on model performance Better data, not more data Active learning shifts focus from the quantity of training data to the quality of training data.

Machine Learning algorithms are ubiquitous, but what is the relationship between our mind and a machine learning algorithm? How can we leverage science to create the change we want to see? The ...

Since early February, the US Department of Defense has employed ML algorithms to identify targets for over 85 air strikes in Iraq and Syria. According to Schuyler ...

Using a well-known algorithm like this makes it easier to benchmark using a developer PC to build and test your own machine learning models.

A team of quantitative traders in London are training their algorithms to invest like Warren Buffett. Unlike many algorithmic trading funds that constantly buy and sell assets, Havelock London ...