TimeSeries.Guru
TimeSeries.Guru is a time series analysis and forecasting software. It allows easy visualization, decomposition, modeling, forecasting, anomaly detection, and more for time series data. The interface is intuitive and it integrates seamlessly with Python and R.
time-series
analysis
forecasting
visualization
anomaly-detection
python
r
TimeSeries.Guru: Time Series Analysis and Forecasting Software
TimeSeries.Guru is a time series analysis and forecasting software. It allows easy visualization, decomposition, modeling, forecasting, anomaly detection, and more for time series data. The interface is intuitive and it integrates seamlessly with Python and R.
What is TimeSeries.Guru?
TimeSeries.Guru is a comprehensive software for time series analysis and forecasting. It provides an easy-to-use interface for visualizing, exploring, analyzing, modeling, forecasting, and monitoring time series data.
Some key features and capabilities include:
- Interactive visualizations like time series plots, seasonality plots, correlation plots, residual plots, etc.
- Decomposition of time series into trend, seasonality, and residuals
- Support for modeling techniques like ARIMA, SARIMA, Exponential Smoothing, Neural Networks
- Forecasting and what-if analysis capabilities
- Anomaly and change point detection algorithms
- Monitoring with alerts and notifications
- Scripting and automation using Python and R APIs
- Connecting to SQL databases, CSV files, and other data sources
- Collaboration features for sharing analysis, models, and insights
Overall, TimeSeries.Guru provides a user-friendly workspace for analyzing time series data at scale. The combination of interactive visualizations and modeling in a single platform makes time series analysis intuitive yet rigorous. With support for both coding and no-coding workflows, it's flexible for users at different skill levels.
TimeSeries.Guru Features
Features
- Visualization of time series data
- Decomposition of time series components
- Forecasting using various models like ARIMA, Prophet, Exponential Smoothing
- Anomaly detection
- Integration with Python and R
Pricing
- Free
- Subscription-Based
Pros
Intuitive interface
Variety of analysis and modeling techniques
Integration with Python and R for extensibility
Cloud-based so no installation needed
Cons
Limited to time series data analysis
Less flexibility than coding models directly in Python/R
Requires uploading data to third-party cloud
Official Links
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