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Effective Communication in Data Science and Use of AI Tools
The chapter stresses the importance of effectively communicating data science results to non-technical stakeholders in a non-production environment by translating technical jargon into understandable terms. It discusses conveying the benefits of using XGBoost models in financial terms and utilizing tools like SHAP for explanation but being cautious about sharing complex plots directly. The conversation also delves into the impact of AI tools like chat GPT on productivity and emphasizes the importance of human decision-making and subject matter expertise in data science roles.