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Types of Machine Learning Systems – Feature-Based and Raw Data-Based (Deep Learning)
In the previous chapters, we learned about data, noise, features, and visualization. Now, it’s time to move on to machine learning models. There is no such thing as one model, but there are plenty of them – starting from the classical models such as random forest to deep learning models for vision systems to generative AI models such as GPT.
The convolutional and GPT models are called deep learning models. Their name comes from the fact that they use raw data as input and the first layers of the models include feature extraction layers. They are also designed to progressively learn more abstract features as the input data moves through these models.
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