In this quickstart we will show you how you can quickly analyze text with Relevance. The data provided is review data of an ecommerce store. With Relevance you can achieve the following:
- Automatically categorize data via clustering. Grouping similar reviews to get a quick overview of the reviews.
- Search against the data, both semantically and traditionally. Finding insights by context and keywords.
- Drilldown with filters. Find trends in customer segments.
- Create charts with aggregates. Visualize trends with charts.
- Extract keywords, sentiment and emotions. Enhance the data with more metrics and segments.
- Label the text dynamically. Categorize data without training with your own provided labels.
First install Relevance AI with models which comes with SentenceTransformers (default vectorizer to create text embeddings).
pip install RelevanceAI[models]
After installation, lets instantiate a client. You will need an API key, which can be found in https://cloud.relevance.ai/sdk/api/.
from relevanceai import Client
# You will be prompted to enter your API KEY
client = Client()