Webinar on “Let’s explore Language Model: Google BERT”
Organized By: WIE IEEE AU SB
Total number of participants: 50participants (approx) .
Date: 19th July 2020
Venue: Google Meet
Speaker: Krupa Galiya
- What is NLP and basics of NLP
- Introduction to BERT. Bidirectional Encoder Representations from Transformers (BERT) is a technique for NLP (Natural Language Processing) pre-training developed by Google.
- History of BERT: BERT has its origins from pre-training contextual representations including Semi-supervised Sequence Learning, Generative Pre-Training, Elmo, and ULMFi Unlike previous models, BERT is a deeply bidirectional, unsupervised language representation, pre-trained using only a plain text corpus
- How to apply the BERT model for search
- Comparison of BERT model with other models.
- Application of BERT: applying BERT models to both ranking and featured snippets in Search
- BERT using Tensorflow