Xfer: an open-source library for neural network transfer learning

Transfer learning is a set of techniques for reusing and repurposing already trained machine learning models in new situations. It brings particular advantages in the domain of deep learning, where training a model from scratch (rather than reusing an existing model) requires a lot of computational and data resources, as well as expertise. This blog post contains a quick overview of transfer learning through the introduction of Xfer, an open-source library that enables easy application and prototyping of transfer learning approaches. Neural networks are machine learning models that learn functions and patterns from data. They underpin numerous modern AI-enabled technologies with applications in conversational agents, self-driving cars, self-learning agents that play board games and many more.