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Functime

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Forecasting with automated ML.
Generated by ChatGPT

Functime is an automated machine learning (AutoML) tool designed for modern-day business forecasting at scale. It allows users to forecast, backtest, and score 100,000 time series in under 10 seconds, which is 100x faster compared to other tools such as Amazon Forecast and u8darts.

Functime is built from the ground up for speed and uses 20x less memory usage. Functime seamlessly integrates holiday, weather, economic, and other external data to support exogenous features and causal analysis, which can be added from API integrations or user-provided datasets.

The tool offers out-of-the-box utilities for adding exogenous features and interpreting every forecast using feature importance plots, Shapley values, and sensitivity analysis.

Functime also features GPT-4-enabled trend-seasonality analysis, which provides a fully customizable and fine-tuned GPT-4 model to describe and justify every prediction.

Visualizations made with the ECharts and Plotly libraries can be shared instantly with other data scientists and business stakeholders or directly embedded into products.

The tool provides blazing-fast hyperparameter tuning and supports embarrassingly-parallel and robust probabilistic forecasts using quantile regression and state-of-the-art conformal prediction techniques.

Additionally, Functime offers zero-inflated and censored forecast options for datasets with messy or numerous zeros. Overall, Functime is a powerful and easy-to-use API for AI/ML forecasting that enables users to run and scale time-series machine learning models in the cloud with ease.

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Functime was manually vetted by our editorial team and was first featured on June 12th 2023.
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2 alternatives to Functime for Business forecasting

Pros and Cons

Pros

Forecast 100,000 time series quickly
100x faster than competitors
20x less memory usage
Integrates various external data
Supports exogenous features
In-built causal analysis tools
Feature importance interpretation
Shapley values analysis
Sensitivity analysis tools
GPT-4 enabled trend-seasonality analysis
Easily shareable visualizations
Embeddable visualizations
Fast feature engineering
Supports embarrassingly-parallel forecasts
Robust probabilistic forecasting
Quantile regression techniques
Conformal prediction techniques
Handles zero-inflated datasets
Handles censored forecasts
Blazing-fast hyperparameter tuning
Scores forecasts in parallel
Supports numerous metrics
Easy-to-use API
Efficiently scales in the cloud

Cons

Requires API or user-provided data
Limited to business forecasting
Heavy reliance on external data
Possible information overload in visualisations
May struggle with messy datasets
Automatic feature engineering complexity
GPT-4 model intricacy
Requires cloud infrastructure
Database bias towards time-series data

Q&A

What is Functime?
What is unique about Functime's speed compared to other tools?
How does Functime integrate external data?
What kind of external data can be integrated with Functime?
What is the purpose of Functime's feature importance plots?
How does Functime use Shapley values and sensitivity analysis?
Can you explain more about the GPT-4-enabled trend-seasonality analysis in Functime?
What kind of visualizations can be created with Functime?
How easy is it to share the visualizations made with Functime?
How does Functime provide fast feature engineering?
How does Functime handle probabilistic forecasts that scale?
What is special about Functime’s zero-inflated and censored forecast options?
How fast is Functime's hyperparameter tuning?
Can Functime run and scale time-series machine learning models in the cloud?
How easy is it to install and use Functime?
How can users backtest with Functime?
What does Functime's 100,000 time series capacity mean for users?
How does Functime handle datasets with messy or numerous zeros?
What metrics does Functime support for scoring forecasts?
Can Functime's visualizations be directly embedded into products?

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