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Outlier detection in production — Part 1
Deploying a Machine Learning (ML) system in production is highly demanded in modern business initiatives. This series of articles provides a big picture of how to successfully build such a process. Our use-case is outlier detection, one of the oldest techniques in ML. It is also among the most used ML applications in the enterprise world.
QUANT AI Lab and Repsol expand their successful collaboration
QUANT AI Lab keeps on growing and expanding to new markets. In March additional experts joined our team to support and complement QUANT´s Data Scientists who have been working at Repsol's Dato Hub since December. Through an analysis of the company’s databases, our...
The importance of having well-calibrated probabilities in AI algorithms
Machine Learning and Artificial Intelligence,algorithms, Big Data and data analysis are on the rise. Every day, more companies are opting to try to obtain information and insights from the data they have stored, or are starting to store. Data that was forgotten in...
Artificial Intelligence vs COVID-19
Is Artificial Intelligence the key to the future after COVID-19? A situation as the one we are currently experiencing serves to, among other things, highlight certain advances: such as Artificial Intelligence. The control and study of the coronavirus is promoting the...