Join three industry experts as they reveal 2025 data and AI trends | Jan 21

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What if you could ask your email client, “Who sent me the link with the latest financial report?” Automated question answering is a human-machine interaction to extract information from data using natural language. This general capability can take many forms,  but one of the most exciting developments has been question answering from unstructured text data, including the massive amounts of information contained in emails, social media posts, blogs, log files, financial statements -- and the list goes on.  Thanks to a series of advances in deep learning techniques in the past two years, question answering capabilities have grown rapidly, and while still emerging, it’s the perfect time to examine how this technology works, when it works well, and where it might still fall short. 

In this webinar we’ll cover
  • General architecture of modern QA systems

  • Deep learning techniques for QA 

  • Guidance on applying these techniques to a practical use case

We’ll also do a live demonstration of a QA prototype that we built. You won’t want to miss it, so we hope to see you there!

Speakers

Data Scientist

Andrew Reed

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Andrew Reed is a Data Scientist at Cloudera Fast Forward Labs where he spends his time implementing machine learning solutions for enterprise clients, researching the latest advances in the field of machine intelligence, and building prototypes applied to real-world use cases. Prior to joining Cloudera, Andrew worked as a Data Scientist in Deloitte’s Analytics & Cognitive practice developing data products and delivering insights for Government and Public Sector organizations. Andrew holds a Bachelor's Degree in Mechanical Engineering from Virginia Tech.

Research Engineer

Melanie Beck

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Melanie Beck is a Research Engineer at Cloudera Fast Forward where she delights in translating machine learning breakthroughs into practical applications, and is particularly interested in natural language processing capabilities. With experience in machine learning and data science at diverse organizations - from manufacturing to cybersecurity - she is a jack-of-all-trades problem solver as well as a reformed astrophysicist, holding a PhD in Astrophysics from the University of Minnesota.

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