Machine learning (ML) versus artificial neural network (ANN)
As mentioned earlier, an ANN is a subset of ML. ANNs are inspired by human understanding; they work as our brain does, composed of different interconnected layers of neurons, where each of them receives information from previous one, processes it, and sends it to the next one until the final output is received. This output could be from a labeled output in the case of supervised learning or certain criteria matching in the case of unsupervised learning.
What are the peculiarities of an ANN? Machine learning is defined as the area in computer science that focuses on trying to find patterns within data sets, and ANN is more oriented toward simulating how human brains are connected to make that work, splitting pattern detection across several layers/nodes that we will call neurons.
Meanwhile, other machine learning algorithms such as support vector machine (SVM) are more popular and established on the object pattern recognition and...
