Neural networks for time series analysis using Deeplearning4j (Day 2)

Recurrent neural networks have proven to be very effective at analyzing time series or sequential data, so how can you apply these benefits to your use case? Tom Hanlon demonstrates how to use Deeplearning4j to build recurrent neural networks for time series data.

Outline

Day 1

• Introduction to neural networks and an overview of the different types of neural networks (feed forward, convolutional, and recurrent)
• Choosing the appropriate neural network for time series data
• Hands-on lab: Generating weather forecasts with a recurrent neural network

Day 2

• Configuring a data ingestion pipeline sequence data
• Recurrent neural nets for the prediction of medical outcomes
• Recurrent neural nets for the classification of sequence data
• Hands-on lab: Sequence classification with recurrent neural networks