Pharma Sales Forecasting Using NLP | Tensorflow | Python |

Overview

Initially, it was necessary to understand the trends and the best way to perform the forecasting based on the requirements. It was necessary to capture any seasonal patterns in the sales and then preserve them for analysis

Solution Overview

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Initial statistical tests were performed to check for seasonality, volatility, and trends.

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ETL Process was performed on the data to suppress noise

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Then various models such as ARIMA, SARIMA, Facebook Prophet were experimented. The best performing model was chosen

Impact

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Ability to forecast monthly, and quarterly sales for a product that would help to make better decisions and informed decisions for each of the products

Technology

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