---
title: Machine Learning Models
slug: litmusedge/product-features/analytics/machine-learning-models
description: The Analytics module allows you to execute your Machine Learning (ML) models “run time”. You can feed live data to the model and get live output from it.
docTags: 
createdAt: 2022-05-13T19:02:44.000Z
---

The Analytics module allows you to upload Machine Learning (ML) models, feed live data into the model, and receive live output from the model.

:::hint{type="info"}
**Note**: To work with ML models in Analytics, your computer has to meet certain [TensorFlow requirements](https://www.tensorflow.org/install/gpu). If it does not, the ML-specific processors will not be available for flow building.
:::

# Create a Machine Learning Model for Upload

To upload a model to Analytics, you need a SavedModel format from [TensorFlow](https://www.tensorflow.org/guide/saved_model). Once you have created and saved a model, you must compress and zip it prior to uploading it to Analytics. SavedModel is a directory containing serialized signatures and the state needed to run them, including variable values and vocabularies. The SavedModel (`saved_model.pb`) file stores the TensorFlow model and a set of named signatures, each identifying a function that accepts tensor inputs and produces tensor outputs. SavedModels may contain multiple variants of the model.

Once your ML model is ready, proceed as follows:

1. Upload the model. See [Upload a Model](docId\:UcNJeNTJsCIN-Zrr2jjtH) for details. 
2. Create an analytics flow based on your model. 
   - TensorFlow processor for time-series data. See [Create an Analytics Flow](docId\:ewmyJSlRbisGimPDgq82A) for details. 
   - TensorFlow Images processor for images. See [TensorFlow Images Processor](docId\:nDGx8TaKLqPyMpRnxq5Ux)for details. 
3. (Optional) Add the Tengo Script processor to modify the model output. See [Tengo Script](docId\:scQMHGGJpMsZENhXn2z4z) for details. 
4. Visualize the ML-based output in the [Flows Manager](docId\:JGhNQYhxbIk8x2nhH5Vte) or through [Applications](docId\:iiPaN4OLp8RQzNJc_Q8br). 

# Access Analytics Models UI

**To access Analytics Models:**

1. Log in to Litmus Edge.
2. From the Navigation panel, navigate to **Analytics **> **Models**.
   The *Models* pane appears. 

::Image[]{src="https://api.archbee.com/api/optimize/SSUUxKZUk9bFTEPNn_6Zo/Emguio_RaNeFVY_6WTcOf_image.png" size="80" width="884" height="460" caption="The Analytics Models pane" position="center" showCaption="true"}

# Next Steps

- [Upload a Model](docId\:UcNJeNTJsCIN-Zrr2jjtH) 
- [Obtain Field Values from a Model](docId\:C2sDFjNL6EpoeymmXZWu3) 
- [Model Types](docId\:d28F1CyHCB3w7n3qQlyEY)