Advanced Sentiment Analysis with NLP Transformers + Vector Search

Sentiment analysis, often known as opinion mining, is a technique used in natural language processing (NLP) to determine the emotional undertone of a text. Organizations use this to identify and group opinions about their product, service, and ideas.

In this video, we will learn how to apply sentiment analysis to huge datasets that can be turned into meaningful query databases rich with insights. We will apply this technique to the hotel industry and understand customer perception and potential improvement areas. To do this, we will:

1. Generate Sentiment labels and scores based on customer reviews.
2. Store them in a Pinecone index as metadata (alongside respective text vectors).
3. Query Pinecone index on selected areas and understand customer opinions.

🌲 Pinecone doc page: https://www.pinecone.io/docs/

Code: https://github.com/pinecone-io/examples/blob/master/learn/analytics-and-ml/data-mining/sentiment-analysis/sentiment-analysis.ipynb

🤖 70% Discount on the NLP With Transformers in Python course: https://bit.ly/3DFvvY5

🎉 Subscribe for Article and Video Updates! https://jamescalam.medium.com/subscribe https://medium.com/@jamescalam/membership

👾 Discord: https://discord.gg/c5QtDB9RAP

00:00 Intro 00:31 What we will build 03:01 Code links and prerequisites 04:16 Dataset download and preprocessing 05:49 Using RoBERTa sentiment analysis model 08:15 Retriever model for building dense vectors 09:39 Create Pinecone vector index 11:40 Sentiment scores, vectors, and indexing 17:35 Sentiment analysis / opinion mining 20:43 Sentiment analysis with specific date range 21:44 Sentiment analysis on specific info 23:58 Final notes

#machinelearning #deeplearning #ai #python ... https://www.youtube.com/watch?v=iIGlAsN1nEs