Types of Machine Learning: Deep Learning

Deep Learning is a branch of Machine Learning specialized in Artificial Neural Networks with multiple intermediary layers. 

Neural Networks with multiple layers can approximate very complex non-linear functions. That’s why Deep Learning has been very successful in CV (Computer Visions), NLP (Natural Language Processing), and Reinforcement Learning. 

Deep Learning architectures include:

  • Convolutional Neural Networks
  • Recurrent Neural Networks 

Due to its ability to learn high-order non-linear functions, Deep Learning algorithms can easily overfit small datasets. Also, Deep Learning algorithms may be computationally expensive, even for a small amount of data.

Thus, Deep Learning is not a silver bullet. Deep Learning can overfit easily with no gain to generalize the solution for simple problems over a small dataset, making it a poor choice for this domain.

However, Deep Learning has achieved stunning results for complex problems that benefit from large amounts of data, longer training time, and intense computational power. 

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