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Description

Weather APIs are designed to provide you with precisely the information you require in your preferred format, encompassing alerts, current conditions, forecasts, weather imagery, and additional features. Acknowledging the significant influence of weather in our daily lives, we simplify the integration of extensive weather data from the most reliable forecaster into your applications, business workflows, or tailored models. Our state-of-the-art, on-demand forecasting engine drives our weather data APIs, which rely on a patented system to synthesize various weather observation data. This unique forecasting system adeptly combines multiple model inputs that are continuously verified in real-time for greater accuracy. Furthermore, our proprietary approach incorporates human forecast management, further enhancing the precision of the data provided. With our on-demand forecast engine platform, you gain access to a wide array of comprehensive weather data resources, featuring a scalable usage model that can be tailored to suit your specific requirements while ensuring reliability. This flexibility empowers users to adapt their weather data needs as they evolve over time.

Description

TimesFM-3 represents an advanced time series foundation model that excels in highly precise multivariate forecasting with a single forward pass. This model, which consists of 330 million parameters, has undergone pre-training on a vast corpus of real-world and synthetic time series data, totaling over 1 trillion time points, thereby enhancing the effectiveness and zero-shot generalization capabilities seen in previous TimesFM iterations. It is adept at simultaneously predicting numerous coevolving time series and understanding dependencies that bolster accuracy without the need for task-specific fine-tuning. Furthermore, it accommodates multiple forecasting targets, including both point and quantile predictions, and incorporates past covariates that are only available historically, alongside dynamic covariates that pertain to future events such as planned promotions, holidays, or weather changes. Utilizing a decoder-only transformer architecture, TimesFM-3 processes sequential data in segments of 32 time steps, employing alternating causal temporal attention and full variate attention to integrate patterns across both time and interrelated series effectively. As a result, it provides a robust tool for forecasting complex time-dependent phenomena in various applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

The Weather Company

Country

United States

Website

www.weathercompany.com/weather-data-apis/

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/

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