Presentation: Two Effective Algorithms for Time Series Forecasting

Track: Predictive Data Pipelines & Architectures

Location: Cyril Magnin I

Duration: 12:50pm - 1:00pm

Day of week: Tuesday

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Abstract

In this 10-minute talk we will explain intuitively fast Fourier transformation and recurrent neural network, two key tools that will be discussed in the later talk. We will also explore how the concepts play critical roles in time series forecasting. The audience of this talk learn what the tools, key concepts associated with them, and why they are useful in time series forecasting.

Note: This is a short talk. Short talks are 10-minute talks designed to offer breadth across the areas of machine learning, artificial intelligence, and data engineering. The short talks are focused on the tools and practices of data science with an eye towards the software engineer.

Speaker: Danny Yuan

Real-time Streaming Lead @Uber

Danny Yuan is a software engineer in Uber. He’s currently working on streaming systems for Uber’s marketplace platform. Prior to joining Uber, he worked on building Netflix’s cloud platform. His work includes predictive autoscaling, distributed tracing service, real-time data pipeline that scaled to process hundreds of billions of events every day, and Netflix’s low-latency crypto services.

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