Deep Learning

Although based on known methods, 10 years ago the party started

Yes, it a a subset of ML, but believe us, it's the main reason of current AI hype

Structured vs. Non-structured information

Traditional ML techniques work very well with what we call 'structured information'

Think of structured information as a classical database table, with columns as attributes and rows as examples or singular elements.

However.... in front of unstructured information traditional ML techniques struggle (images, signals, sounds, etc.)

Even with structured information, someone has to select a collection of features (difficult to get, difficult to define and select etc.). An expert in the problem is required, and many trial an error experiments and evaluations.

Find a good collection of features for a problem is called feature engineering. To find an optimal set of features for a specific problem is difficult (e.g. what symptoms for detecting a disease?)

And, again, in front of unstructured data the problem becomes even harder.

Deep Learning (DL), as a representation learning technique, will try:

• Learn from input samples the rules

• But, at the same time, find and decide what are the features the technique has to pay attention to in order to create the model, with no human interaction at all