Artificial intelligence applied in business today

How machine learning works

Machine learning is the basis of most artificial intelligence solutions.

So how do machines learn? The answer is: from data. In today’s world, huge volumes of data are created in the course of everyday life. From text messages, emails and social media posts to photos and videos taken on phones, massive amounts of information are generated. Millions of sensors create even more data in homes, cars, cities, public transportation infrastructure, and factories. Data scientists can use all that data to train machine learning models that can make predictions and inferences based on the relationships they find in the data.

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Description of anomaly detection

Imagine creating a software system to monitor credit card transactions and detect unusual usage patterns that could indicate fraud. Or an application that tracks activity on an automated production line and identifies errors. Or a race car telemetry system that uses sensors to proactively warn engineers of potential mechanical errors before they occur. These types of scenarios can be solved using anomaly detection, a machine learning-based technique that analyzes data over time and identifies unusual changes. We will now look at how anomaly detection could help in the race car scenario.

1. The car’s sensors collect telemetry data, such as engine revolutions, brake temperature, etc.
2. An anomaly detection model is trained to understand the expected fluctuations in telemetry measurements over time.
3. If a measurement occurs outside the expected normal range, the model reports an anomaly, which can be used to alert the race engineer, who will call the driver to make a stop and fix the problem before he has to quit.