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    Day 1


AI is becoming more prevalent for applications like smart medical devices, robotics, and financial trading, where predictions are made in near real-time. However, there are many complexities associated with managing high-frequency data, the AI modelling approach, and integrating the models in a streaming architecture.

This talk will focus on building a system to address these challenges through:

  • Using a stream processing framework that incorporates time-windowing and manages out-of-order data with Apache Kafka
  • Synchronizing data and managing mathematical assumptions with signal processing techniques
  • Incorporating time requirements when choosing and implementing AI models
  • Updating and caching the models in the system

During the session, we will walk through the process of performing signal processing and time-alignment and designing and deploying a machine learning algorithm for streaming data.

Associated Speakers:

Heather Gorr, PhD

MATLAB Product Manager, Data Science


Associated Talks:

10:20AM - Day 1

View AI for High Frequency Streaming Data

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