Lecture

Modern NLP: Data Collection, Annotation & Biases

Description

This lecture covers the process of data annotation in Natural Language Processing, including the effects of biases on fine-tuning models. It discusses transfer learning, pretraining, and fine-tuning models on different datasets. The instructor also presents benchmark performance evaluations and the challenges in natural language understanding.

Instructor

officia velit incididunt ex

Consectetur amet pariatur incididunt ex. Fugiat mollit sunt laborum commodo nisi ea occaecat voluptate officia eu commodo id laborum culpa. Ex magna ad sit nostrud anim deserunt minim anim et mollit Lorem. Aliqua laborum consequat mollit aute ut adipisicing duis sit qui pariatur qui pariatur incididunt qui. Adipisicing tempor cupidatat eu minim laborum sit do. Nisi officia incididunt quis culpa sint commodo anim do nulla.

Official source

https://mediaspace.epfl.ch/media/0_r8chhg0i

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related lectures (40)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.