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Welcome to our project, where we leverage advanced sentiment analysis techniques to detect and classify toxic content in game-related tweets. Our goal is to develop a predictive model that can accurately identify toxicity based on the language used in these tweets.
This project focuses on analyzing customer churn in a telecommunications company using data-driven techniques to identify at-risk customers and provide actionable insights for improving customer retention.