In a previous couple of articles, we explored some basic machine learning algorithms. Thus far we covered some simple regression algorithms, classification algorithms. We used ML.NET implementation and application of these algorithms. Up to this point, we explored algorithms that are using supervised learning. This means that we always had input and expected output data that we used to train our machine learning models. In this type of learning, the training set contains inputs and desired outputs. This way the algorithm can check its calculated output the same as the desired output and take appropriate actions based on that.

#.net #ai #machine learning #deep learning