CodeNext21′ ML21™ platform for is suitable for finding anomalies in data and can be applied to different types of data.
Anomaly detection explained in “Jip & Janneke language”
An anomaly, also known as an “anomaly,” is a data point that is out of line with previously observed data. If a graph of the data shows a nice line, then you can consider data points that are not on that line as anomalies. However, most data is not too easy to contain in one line (also called a “dimension”). The data companies process sometimes contains as many as millions of data rows, and each row can contain tens to hundreds of dimensions. Such quantities can no longer be analyzed with the naked eye.
Machine Learning makes it possible to automatically find anomalies and do analysis on the data. However, there are many ways to apply ML and look at the data. Depending on what you want to achieve, different techniques and statistical algorithms are available. CodeNext21 has developed new algorithms for its platform and combined them with a unique scalable ML platform design..
Our proprietary machine learning algorithms are “clearbox” and real-time.
ML21™ can be applied for various purposes such as anti-fraud solutions (such as credit card fraud, payment fraud or money laundering fraud) or finding anomalies in processes of manufacturing or logistics. Our platform provides a clear explanation of why the system alarms which enables you to communicate clearly and transparently with your customer.