Nicole
Koenigstein
Data Science/Technology Lead at impactvise.com
"Attention? Attention! - Attention Mechanism In Deep Learning"
"Attention? Attention! - Attention Mechanism In Deep Learning"
08 - 5:30 AM EDT/New York (See in local time)
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05//2026 5:30 AM
05//2026 06:10 AM
America/New_York
#WTGC2026
"Attention? Attention! - Attention Mechanism In Deep Learning"
#WTGC2026
"Attention? Attention! - Attention Mechanism In Deep Learning"
https://www.womentech.net/ringcentral
https://www.womentech.net/ringcentral
"Attention? Attention! - Attention Mechanism In Deep Learning"
"Attention? Attention! - Attention Mechanism In Deep Learning"
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Session: Attention? Attention! - Attention Mechanism In Deep Learning
The concept of attention was first introduced into machine translation in 2015. Nowadays, attention has acquired considerable prominence in the area of artificial intelligence as an essential component of neural networks for a large number of Computer Vision applications, speech recognition and natural language processing, and more recently for time series prediction. To some extent, the attention concept is driven by how we, as humans, direct our visual attention to various areas of a picture, video, or pair of words in a sentence.In this session, you will learn the theory behind the attention mechanism and how to apply it through practical use cases and applications.
Key Takeaways
- Understand the mathmatics behind transformers and attention mechanism
- Learn how to use attention
- Comprehend the key benefits and use cases as to why you should use the attention mechanism
Bio
Nicole Koenigstein is a Data Scientist & Quant- and Data Engineer currently working at impactvise and Nectar Financial. She also reviews machine learning books and online courses for Manning Publications. She is passionate about data science and machine learning. She is dedicated to showing others how to succeed in this field and is committed to making STEM more attractive to women.