About Machine Learning (ML)

The ML dashboard provides a centralized interface for building predictive solutions tailored to various analytical needs. You can create the following types of models:

• Forecasting is a machine learning technique used to predict future values based on historical data, most commonly applied in time series analysis. It is particularly effective when the variation in a target variable depends primarily on time, along with other influencing factors. Common use cases include sales forecasting, stock price prediction, and demand planning. A crucial step in enabling forecasting is selecting an appropriate date or time column, which serves as the temporal reference for the predictions.
• Regression is a modeling technique used to understand the relationship between a target variable and one or more input features, enabling the prediction of continuous numerical values. Common examples include predicting house prices, customer spending, or energy consumption.
• Classification assigns data into predefined categories. It is commonly used in tasks such as spam detection, sentiment analysis, and fraud detection, where the goal is to predict a discrete label or class.

You can either pick from existing trained models and use them for predictions or define and train a new model from scratch by specifying key configurations.

The ML dashboard can be accessed from within workbooks.