Applied Deep Learning for NLP Applications
Repository for talk ODSC talk related to Deep Learning and NLP
Slides to talk: https://github.com/dair-ai/odsc_2020_nlp/blob/master/Applied%20Deep%20Learning%20for%20NLP%20Applications.pdf
Link to talk: https://odsc.com/speakers/applied-deep-learning-for-nlp-applications/
Course Schedule: https://gist.github.com/omarsar/2c68bb9203bea4b5634d534db4f96608
| Topic | Explanation | Notebook |
|---|---|---|
| Part 1 - Introduction to Modern NLP | Introduce the main topics needed to get a bit of understanding of the recent work in NLP. We will start with basic concepts and slowly move into discussing the more recent ideas. | NLP Basics, Deep Learning NLP - Getting Started |
| Part 2 - Training and fine-tuning NLP Models | In this segment we are going to learn how to fine-tune a pretrained language model (DistilRoBERTa) for approaching a downstream task. We will take a look at two popular NLP tasks called sentiment classification and emotion classification. | Emotion Classification |
| Part 3 - Towards building real-world NLP powered applications | In the final segment we are going to look at a simple example of how to leverage pretrained LMs to build a text similarity search application. We will leverage Elasticsearch as a search engine and allow for fast search on sentence representations. | Text Similarity Search Application |