Want to leverage advanced NLP to calculate sentiment?
Can't be bothered building a model from scratch?
Transformers allows you to easily leverage a pre-trained BERT neural network to do exactly that!
In this video we'll go through how to get up and running with Hugging Face Transformers and BERT to be able to calculate sentiment. We'll run the model using a single prompt but also leverage BeautifulSoup to scrape reviews from Yelp to be able to calculate sentiment on a larger scale.
In this video you'll learn how to:
1. Install Transformers
2. Perform Sentiment Scoring using BERT and Python
3. Scrape reviews from Yelp and Calculate their Sentiment
Get the code for this tutorial: [ Ссылка ]
Thanks so much to Mito for sponsoring this video! Mito is an amazing JupyterLab plugin that allows you to work with your data easily using a drag and drop interface that's similar to Excel. Try it out for FREE at trymito.io! If you need a little help getting started, check out the tutorial: [ Ссылка ]
Chapters
0:00 - Start
0:23 - How it Works
1:48 - Tutorial Start
2:55 - Install and Import Dependencies
9:20 - Setup BERT and Transformers Neural Network
11:27 - Encode Sentences for Modelling and Calculate Sentiment
16:40 - Scrape Reviews from Yelp using BeautifulSoup
22:41 - Load Reviews into Pandas and Calculate Sentiment
29:52 - Run the Sentiment Pipeline for Multiple Reviews
31:32 - Wrap Up
Oh, and don't forget to connect with me!
LinkedIn: [ Ссылка ]
Facebook: [ Ссылка ]
GitHub: [ Ссылка ]
Patreon: [ Ссылка ]
Join the Discussion on Discord: [ Ссылка ]
Happy coding!
Nick
P.s. Let me know how you go and drop a comment if you need a hand!
