A Quick Look At Deep Learning

A subset of machine learning, deep learning has been around since the middle of the last century, but started evolving rapidly since the early 21st century. Generative Al and ChatGPT have brought the focus back on it. We take a look at what deep learning is about and how it's being used

- Bala Kalavala

Data management is one of the hardest and costliest tasks every organisation is faced with. The fact that organisations appoint a chief data officer (CDO) shows how much importance they give to managing data — its treatment, classification, analytics, security and compliance requirements, etc. This is where deep learning (DL) shines as a perfect data management strategy when employed with the right set of tools.

While DL has been around for a while, the recent popularity of ChatGPT brings it back to being a hot topic in the world of AI. Deep learning is a subset of machine learning (ML), and is based on how the human brain is structured and works. If you are new to the subject and looking to learn the differences between AI, ML and DL, check out my writing mentioned in the ‘References’ at the end of this article. DL uses artificial neural networks to learn from large amounts of data. It gets the name ‘deep’ because it leverages multiple layers of interconnected neurons to process and learn from the data. DL algorithms are capable of learning complex patterns in images, audio and text. Deep learning uses large amounts of unlabelled data to learn the underlying structure and patterns in data. It is an unsupervised learning module that does not require labelled data to start learning from.