Deploying Distributed AI and Machine Learning in Financial Services

Presented by

Dmitry Baev, Vice President of Solutions Engineering at

About this talk

The Financial Services industry has the potential to benefit from advanced application of Machine Learning and Artificial Intelligence by leveraging their vast data reserves in order to transform their businesses. However, keeping pace with new technologies for data science and Machine Learning can be overwhelming. Financial Services industry regulations can make it even more challenging to deploy and manage Machine Learning applications in large-scale distributed environments. In this talk we will cover how to leverage your existing Big Data investment to deliver leading edge data science using H2O. We will look at real customer use cases for AI and ML in Financial Services and discuss how to overcome deployment challenges in distributed Big Data environments in order to deliver transformational business results and faster time-to-value. Join this talk to learn how Financial Services organizations are extracting real business value with AI and ML. - How to train Machine Learning models at scale using distributed Big Data platforms - How to apply Automated Machine Learning (AutoML) to accelerate your model development pipelines - How to deploy Machine Learning models into production environments - AI in Financial Services success stories Presenter: Dmitry Baev, Vice President of Solutions Engineering at
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