Estimating Utility from Cannabis with Sentiment Analysis | Cannabis Data Science #70
😊 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
