Part 3/9:
The brain adeptly tackles this nuisance variation, but early machine learning models struggled to disentangle complex patterns effectively. To illustrate, envision two intertwined manifolds representing distinct categories such as cars and airplanes. The goal is to separate these manifolds using simple linear classifiers, which becomes difficult due to their non-linear nature. Thus, deep learning aims to build models that can effectively disentangle these complex data representations.