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Deep Learning for speech recognition & Compressing neural nets for IoT devices

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Paul R. and Bella D.
Deep Learning for speech recognition & Compressing neural nets for IoT devices

Details

Speech Recognition:
Speech recognition is invading our lives. It’s built into our phones, our game consoles and our smart watches. It’s even automating our homes. But speech recognition has been around for decades, so why is it just now hitting the mainstream? In the first session we will show how deep learning finally made speech recognition accurate enough to be useful outside of carefully controlled environments.

Compressing Neural Nets:
We have reached a period in which Computer Vision tasks are almost solved using Deep-Learning techniques but some open questions still remain around practical usage of these techniques, specifically in IoT applications. In the second part of the lecture we will cover how to compress Deep neural nets to fit IoT edge devices.

Speaker Bio:
Alan Bekker is a Phd researcher and an author of papers in leading artificial intelligence journals and conferences, mostly focusing on applications of deep learning.
https://alanbekker.wordpress.com/

Target Audience:
Some basic deep learning background is needed

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Kiryat Atidim, Tel Aviv · Tel Aviv-Yafo