Machine learning (ML) with neural networks is enabling exciting new inference capabilities for software. Typically, ML models have run in the cloud, which meant that, to make a classification or prediction, you needed to send the text, sound, or images over the...
Machine Learning (ML) is quickly becoming a common feature in everyday computer interactions, and we often don’t even realize it. One example is ML-based image recognition for camera apps, such as the app introduced in the article “Face Detection on...
Introduction Machine learning is not at all a new concept, but its actual implementation is still far from reality for many businesses. Why? When they have big data problems, enterprises typically hire experts from different domains to help the data engineers in...
Introduction Neural Networks (NN) technology is one of the most used approaches in modern Artificial Intelligence (AI). It has been applied successfully to solving such problems as forecasting, adaptive control, recognition classification, and many others. An...
Introduction Let’s say we want to group some data. Each data element has some (numeric) attributes. Using these attributes, we want to split the data into different clusters. For us humans this often can be done just by looking at the data. For a computer, this...
The world is full of complex, dynamical systems, from climate changes and tides to the route of the solar system around the galaxy. Our lives are also full of dynamical systems: fluctuations of the economy, the local and global trade, social dynamics, or the behavior...
