So far in our journey through Machine Learning with ML.NET, we used different machine learning algorithms to solve various tasks. Usually, at the end of each tutorial, we showed some metrics that determine how well the algorithms performed, but we haven’t...
In one of the previous articles, we explored image classification as one of the most common computer vision problems. However, this type of problem is not applicable to more complex projects, like let’s say self-driving cars. Problems from the real world usually...
It is always fun and educational to read deep learning scientific papers. Especially if it is in the area of the current project that you are working on. However, often these papers contain architectures and solutions that are hard to train. Especially if you want to...
From Netflix, Google, and Amazon, to smaller webshops, recommendation systems are everywhere. In fact, this type of system represents probably one of the most successful business applications of Machine Learning. Their ability to predict what users would like to read,...
In a previous couple of articles, we explored some basic machine learning algorithms and how they fit into the .NET world. Thus far we covered some simple regression algorithms, classification algorithms. Apart from that, we learned a bit about unsupervised learning,...
In a previous couple of articles, we explored some basic machine learning algorithms and how they fit into the .NET world. Thus far we covered some simple regression algorithms, classification algorithms. Apart from that, we learned a bit about unsupervised learning,...