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TensorFlow machine learning with financial data on Google Cloud Platform

March 2, 2016
Corrie Elston

Solutions Architect, Google Cloud Platform

If you knew what happened in the London markets, how accurately could you predict what will happen in New York? It turns out, this is a great scenario to be tackled by machine learning!

The premise for this problem is that by following the sun and using data from markets that close earlier, such as London that closes 4.5 hours ahead of New York, you could more accurately predict market behaviors 7 out of 10 times.

We’ve published a new solution, TensorFlow Machine Learning with Financial Data on Google Cloud Platform, that looks at this problem. We hope you’ll enjoy exploring it with us interactively in the Google Cloud Datalab notebook we provide.

As you go through the solution, you’ll query six years of time series data for eight different markets using Google BigQuery, explore that data using Cloud Datalab, then produce two powerful TensorFlow models on Cloud Platform.

TensorFlow is Google’s next generation machine learning library, allowing you to build high performance, state-of-the-art, scalable deep learning models. Cloud Platform provides the compute and storage on demand required to build, train and test those models. The two together are a marriage made in heaven and can provide a tremendous force multiplier for your business.

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This solution is intended to illustrate the capabilities of Cloud Platform and TensorFlow for fast, interactive, iterative data analysis and machine learning. It does not offer any advice on financial markets or trading strategies. The scenario presented in the tutorial is an example. Don't use this code to make investment decisions.

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