5, 10 or 20 seats+ for your team - learn more
In this liveProject you’ll use scikit-learn’s non-negative matrix factorization algorithm to perform topic modeling on a dataset of Twitter posts. You’ll step into the role of a data scientist tasked with summarizing Twitter discussions for the customer support team of an airline company and use this powerful algorithm to rapidly make sense of a large and complex text corpus. You’ll build a text preprocessing pipeline from scratch, visualize topic models, and finally compile a report of support topics for the customer services team.
This liveProject is for data scientists and developers who are confident programming with Python and the Python data ecosystem. To begin this liveProject you will need to be familiar with the following:
In this liveProject, you’ll master topic modeling—an amazing skill for quickly analyzing textual datasets. You’ll learn the ins and outs of applying the NMF algorithm in a real-world setting:
geekle is based on a wordle clone.