Technical Blog

Qeexo AutoML supports three one-class classification algorithms widely used for anomaly/outlier detection; Isolation Forest, Local Outlier Factor, and One-class Support Vector Machine. These algorithms build models by learning from only one class of data....

In industrial environments, it is often important to be able to recognize when a machine needs to be serviced before the machine experiences a critical failure. This type of problem is often called predictive maintenance. One approach to solving predictiv...

Qeexo’s AutoML enables Machine Learning and AI applications development for a range of sensors. A comprehensive list of sensors includes Accelerometer, Gyroscope, Magnetometer, Temperature, Pressure, Humidity, Microphone, Doppler Radar, Geophone, Colori...

We would like to build a machine learning model to distinguish between the following three classes: "X", "O", "No Gesture". This blog describes building the Air Gesture with Arduino Nano 33 BLE Sense. You can also build the same using any of the boards a...

In machine learning, the quality of feature selection strongly affects the quality of the trained model. Feature selections approaches differ depending on the type of machine learning problem, e.g., supervised learning or unsupervised learning. F...

Deep learning (DL) has gradually become one of the most popular areas in artificial intelligence after the 1990s. Deep learning is a branch of machine learning and uses neural layers to build models. It combines low-level features and gradually forms abst...

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Try Qeexo AutoML

Register for a free evaluation or other SaaS options.