Forecast
Advanced zero-shot forecasting capabilities for time series data
TimeGPT offers advanced zero-shot forecasting capabilities for a wide range of time series domains, thanks to its large-scale and diverse pretraining.
Overview
Overview
This section provides an overview of forecasting features available in TimeGPT. You can leverage TimeGPT for:
- Zero-shot forecasting
- Forecasting with exogenous variables
- Manipulating holidays and special dates
- Incorporating categorical variables
- Long-horizon forecasting
- Forecasting multiple series
- Fine-tuning TimeGPT
- Working with specific loss functions
- Cross-validation
- Adding prediction intervals
- Handling irregular timestamps
These capabilities allow teams to handle real-world scenarios across different industries and problem domains.
When to Use TimeGPT for Forecasting
When to Use TimeGPT for Forecasting
TimeGPT is a powerful choice when you need:
- Rapid iteration without explicit training on your own datasets.
- A flexible model that generalizes well across different time series scenarios.
- Support for additional context or features like holidays, external events, or categorical data.
Key Feature: Zero-Shot Forecasting
Zero-shot forecasting lets you generate predictions without having to train a new model from scratch on your data. This can significantly reduce your time to production for new or changing forecasting tasks.
Key Feature: Fine-Tuning
Gain performance boosts by fine-tuning TimeGPT on your own dataset or by leveraging specific loss functions. This approach helps tailor the model to your unique forecasting requirements.
By combining zero-shot approaches with optional fine-tuning, TimeGPT offers a robust and efficient solution for time series forecasting.
1. Zero-Shot Forecasting
Zero-shot forecasting is an excellent starting point for quick insights.
For detailed instructions, see: Zero-shot forecasting documentation.
2. Add Exogenous Variables
If you have additional external drivers or explanatory factors, include them to improve predictions.
For more details, visit: Forecasting with exogenous variables.
3. Incorporate Holidays or Special Dates
Holidays and special dates can have significant impact on time series signals.
Learn how to handle them here: Forecasting with holidays and special dates.
Forecasting with Categorical Variables
Forecasting with Categorical Variables
Explore how to add categorical information and improve your forecasts:
Forecasting with categorical variables.
Long-Horizon Forecasting
Long-Horizon Forecasting
Learn best practices for forecasting extended time periods well into the future:
Long-horizon forecasting.
Forecasting Multiple Series
Forecasting Multiple Series
Handle multiple time series simultaneously to build scalable and efficient solutions:
Forecasting multiple series.
Forecasting with Categorical Variables
Forecasting with Categorical Variables
Explore how to add categorical information and improve your forecasts:
Forecasting with categorical variables.
Long-Horizon Forecasting
Long-Horizon Forecasting
Learn best practices for forecasting extended time periods well into the future:
Long-horizon forecasting.
Forecasting Multiple Series
Forecasting Multiple Series
Handle multiple time series simultaneously to build scalable and efficient solutions:
Forecasting multiple series.
Fine-Tuning TimeGPT
Fine-Tuning TimeGPT
Adapt TimeGPT to your specific domain or data distribution:
Fine-tuning TimeGPT.
Custom Loss Functions
Custom Loss Functions
Go beyond default metrics by defining custom loss functions:
Fine-tuning with a specific loss function.
Cross-Validation
Cross-Validation
Ensure robust forecasting performance through cross-validation:
Cross-validation.
Prediction Intervals
Prediction Intervals
Build prediction intervals to quantify uncertainty in your forecasts:
Adding prediction intervals.
Irregular Timestamps
Irregular Timestamps
Discover approaches to deal with missing or irregular time steps:
Handling irregular timestamps.
Below is a concise code snippet to get started with zero-shot forecasting. This example demonstrates how to import TimeGPT and make a simple prediction.
Visual depiction of a sample zero-shot forecast with TimeGPT
Congratulations! You are now equipped with TimeGPT’s key forecasting features. Explore the linked guides for detailed instructions on advanced topics.