Introduction to Transfer Learning and Pre-Trained Models

Just as one wouldn’t try to reinvent the wheel, in the world of data science and machine learning (ML), it’s often more efficient to build upon existing knowledge. This is where the concepts of transfer learning (TL) and pre-trained models come into play, two incredibly important tools in a data scientist’s repertoire.

TL is almost like a shortcut in ML. Instead of taking a model architecture that has never seen data before, such as a Logistic Regression model or a Random Forest model, imagine being able to take a model trained on one task and then repurposing it for a different, yet related task. That’s TL in a nutshell – leveraging existing knowledge to learn new things more efficiently. It’s a concept that echoes throughout many facets of life and is a key technique in data science.

Pre-trained models are off-the-shelf components, ready to be used right out of the box. They&...