From the course: Advanced Python in Excel: Machine Learning
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Predictive analytics for financial forecasting
From the course: Advanced Python in Excel: Machine Learning
Predictive analytics for financial forecasting
- [Narrator] Predictive analytics is a very powerful tool for financial forecasting. It uses historical data and machine learning models to predict future financial outcomes. This can help businesses make informed decisions. In finance, predictive analytics can be applied to different areas, such as revenue forecasting, expense management, and investment strategy. Accurate forecast can significantly impact a company success. The first step in predictive analytics is data collection. Gathering historical data on key financial metrics is crucial. This data will serve as the foundation for building accurate and reliable models. Data cleaning and preparation will follow. This involves handling missing values, removing outliers, and transforming data into a format suitable for analysis. For this, clean data is essential. Then we have feature engineering. Creating relevant features from raw data helps improve the model performance. For example, generating lagged variables or moving averages…
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