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At Finative, an ESG analytics company, you’re a data scientist who helps measure the sustainability of publicly traded companies by analyzing environmental, social, and governance (ESG) factors so Finative can report back to its clients. Recently, the CEO has decided that Finative should increase its own sustainability. You’ve been assigned the task of saving digital storage space by storing only relevant data. You’ll test different methods—including keyword retrieval with TD-IDF, computing cosine similarity, and latent semantic analysis—to find relevant keywords in documents and determine whether the documents should be discarded or saved for use in training your ML models.
This liveProject is for ML engineers, intermediate-level Python programmers, and early-stage data scientists who are familiar with the basics of linear algebra. To begin these liveProjects you’ll need to be familiar with the following:TOOLS
In this liveProject, you’ll learn how to preprocess text data using NLP tools, including regular expressions, tokenization, and stop-word removal.
geekle is based on a wordle clone.