INTRO TO DATA SCIENCE

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Introduction to data science notes pdf
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september 2025

2024/2025
This data science document presents an analysis of retail sales data to forecast future demand. Using historical sales records from 2018–2024, we performed EDA, time-series modeling, and machine learning techniques (ARIMA, LSTM). The models showed that seasonal trends strongly influence sales, with LSTM achieving the lowest error rate. The findings can guide inventory planning and reduce stockouts. Future work includes integrating external factors like weather and promotions.”
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