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Real-time Streaming for Machine Learning

This tutorial demonstrates the availability of streaming data in a data science environment, which is useful for working with real-time and fresh datasets.

First, we collect data from an existing Kafka stream into an Iguazio time series table. Next, we visualize the stream with a Grafana dashboard; and finally, we access the data in a Jupyter notebook using Python code.

We use a Nuclio serverless function to “listen” to a Kafka stream and then ingest its events into our time series table. Iguazio gets you started with a template for Kafka to time series.

We visualize the data with Grafana and work with time series data using Python code in Jupyter. Data scientist easily access both historical and real-time data in a full Python environment for exploration and training with Iguazio.

Stream data into your Jupyter notebook on Iguazio’s Data Science Platform by signing up for a free trial.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.