Summary
Transfer learning, where a model is first pre-trained on a data-rich task before being fine-tuned on a downstream task, has emerged as a powerful technique in natural language processing (NLP). The effectiveness of transfer learning has given rise to a diversity of approaches, methodology, and practice. In this session, we explore the landscape of transfer learning techniques for NLP by introducing a unified framework that converts all text-based language problems into a text-to-text format.
Requirements
Join the AI Maker Community Slack Workspace: The communication during the session will happen through our Slack Workspace, in the #ai-maker-sessions channel: https://join.aimaker.community
Please register for this free event on Eventbrite.
Event Details
This is an online event. We will post a link to the session in Slack shortly before the session starts.