Time Series Libraries
Libraries specialized in analyzing and forecasting time series data.
Supported Solution Fields
When to Use
- When you need to analyze temporal patterns
- When you have sequential data
- When you need to handle seasonality and trends
When Not to Use
- When your data isn't time-dependent
- When you need real-time predictions
- When you have non-sequential data
Tradeoffs
- Accuracy vs Speed: More complex models take longer to train
- Flexibility vs Complexity: More features mean steeper learning curve
- Memory vs Performance: Longer sequences require more resources
Commercial Implementations
-
Prophet
- Facebook's time series forecasting tool
- Handles missing data and outliers
- Good for business forecasting
-
statsmodels
- Statistical modeling library
- Comprehensive time series tools
- Academic/research focus
-
Tiny Time Mixers (TTM)
- 1M parameter foundation model
- CPU-trainable
- Strong interpretability
- Best-in-class performance
- Supports 1-min to 1-hour periods
-
Moment
- Family of foundation models (37M-346M params)
- Multiple time series tasks
- Strong academic backing
- Comprehensive tutorials
Common Combinations
- Financial analysis systems
- Demand forecasting
- Resource planning
Case Study: Sales Forecasting
A retail company implemented time series forecasting:
Challenge
- Seasonal sales patterns
- Multiple product lines
- Variable demand
Solution
- Implemented Prophet
- Incorporated seasonal patterns
- Added custom features
Results
- 25% more accurate forecasts
- Better inventory management