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Deep Learning for Live-Cell Imaging with David Van Valen - TWiML Talk #141

Deep Learning for Live-Cell Imaging with David Van Valen - TWiML Talk #141

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)


Deep Learning for Live-Cell Imaging with David Van Valen - TWiML Talk #141

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

ratings:
Length:
37 minutes
Released:
May 22, 2018
Format:
Podcast episode

Description

In today’s show, I sit down with David Van Valen, assistant professor of Bioengineering & Biology at Caltech. David joined me after his talk at the Figure Eight TrainAI conference to chat about his research using image recognition and segmentation techniques in biological settings. In particular, we discuss his use of deep learning to automate the analysis of individual cells in live-cell imaging experiments. We had a really interesting discussion around the various practicalities he’s learned about training deep neural networks for image analysis, and he shares some great insights into which of the techniques from the deep learning research have worked for him and which haven’t. If you’re a fan of our Nerd Alert shows, you’ll really like this one. Enjoy! The notes for this show can be found at twimlai.com/talk/141. For more information on this series, visit twimlai.com/trainai2018.
Released:
May 22, 2018
Format:
Podcast episode

Titles in the series (100)

This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders. These creators, builders, makers and influencers value TWiML as an authentic, trusted and insightful guide to all that’s interesting and important in the world of machine learning and AI. Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.