Machine translation helps break our language barrier
Who is this presentation for?Non-technical or Business audience
Over the last few years, a multitude of customers have come with various machine translation use cases. Here are a few examples: identify which language is being spoken or typed, how to translate one language to another, and how to transliterate text from one language to another. Hard problems such as these and many more like them are now readily solved using advanced APIs that are readily available.
Jaya Mathew provides a brief introduction to machine translation (MT) and the evolution and application of MT. You’ll focus on neural machine translation (NMT). Jaya explores some of the typical customer cases and how to embed such functionality in your application. You’ll see a Python-based solution demo and some resources and tools that can help you as you continue to explore the domain.
What you'll learn
- Discover how to quickly apply MT in your applications
- Improve your understanding of MT
- Learn to qualify new opportunities and assess their fit for MT and smoothly embed MT using APIs in your applications
Jaya Susan Mathew
Jaya Mathew is a senior data scientist on the artificial intelligence and research team at Microsoft, where she focuses on the deployment of AI and ML solutions to solve real business problems for customers in multiple domains. Previously, she worked on analytics and machine learning at Nokia and Hewlett Packard Enterprise. Jaya holds an undergraduate degree in mathematics and a graduate degree in statistics from the University of Texas at Austin.
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