Connect BigML and Neo4j to Build Intelligent Automations
Choose a Trigger
When this happens...
New Resource
Choose an Action
Automatically do this!
- Request a new Action for Neo4j
Enable Integrations or automations with these events of BigML and Neo4j
Enable Integrations or automations with these events of BigML and Neo4j
Triggers
New Resource
Triggers when a new resource is created
Actions
Create Anomaly Score
Calculates the anomaly score of a data instance.
Create Centroid
Find out the closest cluster to your data instance
Create Prediction
Predict using a model , logistic regression or deepnets
Find Resource
Finds a resource
List Sources
Get all the sources.
List Datasets
Get all the dataset.
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Frequently Asked Questions
To start, connect both your BigML and Neo4j accounts to viaSocket. Once connected, you can set up a workflow where an event in BigML triggers actions in Neo4j (or vice versa).
Absolutely. You can customize how BigML data is recorded in Neo4j. This includes choosing which data fields go into which fields of Neo4j, setting up custom formats, and filtering out unwanted information.
The data sync between BigML and Neo4j 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 BigML and Neo4j. 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 BigML
BigML is a leading machine learning platform that provides a wide range of tools and services for creating, deploying, and managing machine learning models. It offers an intuitive interface and powerful APIs to help businesses and developers harness the power of machine learning for predictive analytics, anomaly detection, clustering, and more.
Learn MoreAbout Neo4j
Neo4j is a leading graph database platform that enables organizations to unlock the value of connections, influences, and relationships in data. It is designed to handle highly connected data and is used for a variety of applications such as fraud detection, real-time recommendations, and network management.
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