What's included

• Predictive Model / Forecasting Model

  A predictive model is a statistical or machine learning approach used to analyze historical data and make predictions about future outcomes. It identifies patterns and relationships in data to estimate the likelihood of future events. Common techniques include regression analysis, decision trees, neural networks, and ensemble models. Predictive modeling is widely used in various fields such as finance (credit scoring), healthcare (disease prediction), marketing (customer behavior analysis), and risk management. A forecasting model is a type of predictive model specifically designed to predict future values based on historical time-series data. It is commonly used to estimate trends, patterns, and seasonality in areas like sales forecasting, weather prediction, stock market trends, and demand planning. Popular forecasting techniques include ARIMA (AutoRegressive Integrated Moving Average), exponential smoothing, and deep learning models like LSTMs (Long Short-Term Memory networks).