https://github.com/dalelane/event-streams-tensorflow

Example of using TensorFlow with IBM Event Streams
https://github.com/dalelane/event-streams-tensorflow

Last synced: about 2 months ago
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Example of using TensorFlow with IBM Event Streams

• Host: GitHub
• URL: https://github.com/dalelane/event-streams-tensorflow
• Owner: dalelane
• Created: 2019-10-31T00:20:45.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T06:48:01.000Z (about 2 years ago)
• Last Synced: 2024-10-14T10:34:25.351Z (3 months ago)
• Language: Python
• Homepage: https://dalelane.co.uk/blog/?p=3924
• Size: 21.5 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

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README

        
# event-streams-tensorflow

**Example of using TensorFlow with IBM Event Streams, to explain how to get started creating machine learning applications using the data you have on Kafka topics.**

This is a simple demo app, not intended for production use (there is no error-handling at all, the ML model isn't hosted, etc.). The aim is to provide an easy-to-understand working example of how to integrate Kafka with TensorFlow.

I've explained how it all works in **https://dalelane.co.uk/blog/?p=3924** 

It's written for Python 3. To run it:

1. `pip install -r requirements.txt`

2. Edit `config.env` with the properties of your cluster 

3. Run `run-step-0.sh` to set up your Kafka topics

4. Run `run-step-1.sh` to train a machine learning model using data from a Kafka training topic

5. Run `run-step-2.sh` to train a machine learning model and use it to classify an image

6. Run `run-step-3.sh` to train a machine learning model and test it using data from a Kafka test topic

7. Run `run-step-4.sh` to use a machine learning model to classify a stream of events on a Kafka topic

To wipe everything if you want to start again, run `run-cleanup-99.sh`.