Documentation
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Momentum
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MLOps
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Impulse EDW
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- 2.1 Create a Warehouse
- 2.2 Edit Warehouse
- 2.3 Datasources In Warehouse
- 2.4 Ingesting Data Into Tables or Datasources
- 2.4.1 Ingesting From Momentum Data Pipeline
- 2.4.2 Uploading File Using Impulse UI
- 2.4.3 Ingesting From External File/Storage System
- 2.5 Add Data to Existing Tables
- 2.5.1 Update Existing Index
- 2.6 Delete Table Records (Rows)
- 2.7 Delete Tables or Datasources
- 2.8 Monitoring Indexing Tasks
- 2.9 View Datasource Stats
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Inset BI
- Alerts and Reports
- Connecting to a new database
- Registering a new table
- Creating charts in Explore view
- Manage access to Dashboards
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- Articles coming soon
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- Articles coming soon
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- Articles coming soon
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- Articles coming soon
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- Articles coming soon
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APIs
- Articles coming soon
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3.1 Machine Learning
Momentum is a machine learning automation platform. It has implementation of commonly used machine learning algorithms – supervised, unsupervised, reinforcement learning and recommendation engine. Momentum allows training ML models using drag-and-drop and UI-based approach without writing any code. The following section describes how to train a model, use the trained model for prediction and deploy it to MLOps. Regardless of the algorithm type, the process of training, prediction and deployment is the same for all ML types.
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