Neural nets vulnerable to hackers

Neural nets trained on sensitive data, like medical data or social security numbers, can “accidentally” memorize it, leaving it vulnerable to hackers.

“We hope to raise awareness that it’s important to consider protecting users’ sensitive data as machine learning models are trained. Machine learning or deep learning models could be remembering sensitive data if no special care is taken.”

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AI, Machine Learning, advanced analytics in the enterprise environment Part 2 (theory)

There is a lot of discussions the past years about the revolution predictive analytics will bring to the businesses. But, predictive analytics is not something new. It used to be a part of statistics! Corporations with the resources were doing it for decades. Nowadays, however, it is more accessible, due to technological advancements in the areas of computing power, software and storage, the abundance of big datasets, and advances in algorithm research. Any student can now use the cloud to perform an experiment that a few years ago would have been possible to be performed only by large corporations or government agencies.

The challenge is how can we apply advanced analytics, and AI in an enterprise environment, efficiently and effectively.

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AI, Machine Learning, advanced analytics in the enterprise environment Part 1 (a personal story from the 90s)

The first time I saw predictive analytics live, in praxis, to provide useful information was in the mid-90s. As a student and aspiring engineer, I was enrolled in a Total Quality/Six Sigma class. During a field trip we visited a Japanese run, car manufacturing plant where, to my astonishment, blue-collar workers were applying regression in order to predict when to change tools!

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