Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Transformers: Text Classification for NLP Using BERT

via LinkedIn Learning

Go to class Write review

Coursera

Gain a Splash of New Skills - Coursera+ Annual Nearly 45% Off

CodeSignal

Introduction to Programming with Python

Overview

Coursera Flash Sale

40% Off Coursera Plus for 3 Months!

Learn about transformers, the go-to architecture for NLP and computer vision tasks.

Syllabus

Introduction

Natural language processing with transformers
How to use the exercise files

1. NLP and Transformers

How transformers are used in NLP
Transformers in production
Transformers history
Challenge: BERT model sizes
Solution: BERT model sizes

2. BERT and Transfer Learning

Bias in BERT
How was BERT trained?
Transfer learning

3. Transformer Architecture and BERT

Transformer: Architecture overview
BERT model and tokenization
Positional encodings and segment embeddings
Tokenizers
Self-attention
Multi-head attention and feedforward network

4. Text Classification

BERT and text classification
The Datasets library
Overview of IMDb dataset
Using a tokenizer
Tiny IMDb
A training run

Conclusion

Additional training runs

Taught by

Jonathan Fernandes

Reviews

4.7 rating at LinkedIn Learning based on 456 ratings

Start your review of Transformers: Text Classification for NLP Using BERT