😊 In this long-awaited episode, we use natural language processing (NLP) to rank strain reviews by consumer and examine whether certain compounds are related to the review rankings. We build a model that you can use to determine if any specific compounds have a positive or negative relationship with the sentiment of consumer reviews. Follow along as we:1. Prepare and visualize strain and lab result data in Python.2. Perform sentiment analysis using the Natural Language Toolkit (nltk).3. Create utility functions with THC, CBD, and terpenes as preferences.🤝 Join the fun, data wrangling, and analytics in the Cannabis Data Science meetup, every Wednesday at 8:30am PST | 10:30am CDT | 11:30am EST. https://www.meetup.com/cannabis-data-science/🧑‍💻 Find the data and source code: https://github.com/cannlytics/cannabis-data-science💸 Support the group: https://opencollective.com/cannlytics-company🔥 Check out Cannlytics: https://cannlytics.com