Connect VLM Run and Numerai to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for VLM Run
Choose an Action
Automatically do this!
- Request a new Action for Numerai
Enable Integrations or automations with these events of VLM Run and Numerai
Enable Integrations or automations with these events of VLM Run and Numerai
Actions
Image to json
Generate structured prediction for the given image.
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Frequently Asked Questions
To start, connect both your VLM Run and Numerai accounts to viaSocket. Once connected, you can set up a workflow where an event in VLM Run triggers actions in Numerai (or vice versa).
Absolutely. You can customize how VLM Run data is recorded in Numerai. This includes choosing which data fields go into which fields of Numerai, setting up custom formats, and filtering out unwanted information.
The data sync between VLM Run and Numerai typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between VLM Run and Numerai. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About VLM Run
VLM Run is a platform designed to enhance your running experience by providing tools and resources for tracking, analyzing, and improving your running performance. Whether you're a beginner or a seasoned marathoner, VLM Run offers features to help you set goals, monitor progress, and connect with a community of runners.
Learn MoreAbout Numerai
Numerai is a unique hedge fund that leverages the power of data science and machine learning to make stock market predictions. It operates as a decentralized network where data scientists from around the world can contribute their models to improve the fund's performance. By using encrypted data, Numerai ensures privacy and security while fostering collaboration among its community of data scientists.
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