Deep Learning for NLP: From the Trenches with Charlene Chambliss - #433

Deep Learning for NLP: From the Trenches with Charlene Chambliss - #433

Today we’re joined by Charlene Chambliss, Machine Learning Engineer at Primer AI. Charlene, who we also had the pleasure of hosting at NLP Office Hours during TWIMLfest, is back to share some of the work she’s been doing with NLP. In our conversation, we explore her experiences working with newer NLP models and tools like BERT and HuggingFace, as well as whats she’s learned along the way with word embeddings, labeling tasks, debugging, and more. We also focus on a few of her projects, like her popular multi-lingual BERT project, and a COVID-19 classifier. Finally, Charlene shares her experience getting into data science and machine learning coming from a non-technical background, and what the transition was like, and tips for people looking to make a similar shift.

Episoder(781)

Computer Vision for Cozmo, the Cutest Toy Robot Everrrrr! with Andrew Stein - TWiML Talk #102

Computer Vision for Cozmo, the Cutest Toy Robot Everrrrr! with Andrew Stein - TWiML Talk #102

In this episode, I'm joined by Andrew Stein, computer vision engineer at consumer robotics company Anki, and his partner in crime Cozmo, a toy robot with tons of personality. Andrew joined me during t...

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Expectation Maximization, Gaussian Mixtures & Belief Propagation, OH MY! w/ Inmar Givoni - Talk #101

Expectation Maximization, Gaussian Mixtures & Belief Propagation, OH MY! w/ Inmar Givoni - Talk #101

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A Linear-Time Kernel Goodness-of-Fit Test - NIPS Best Paper '17 - TWiML Talk #100

A Linear-Time Kernel Goodness-of-Fit Test - NIPS Best Paper '17 - TWiML Talk #100

In this episode, I speak with Arthur Gretton, Wittawat Jitkrittum, Zoltan Szabo and Kenji Fukumizu, who, alongside Wenkai Xu authored the 2017 NIPS Best Paper Award winner “A Linear-Time Kernel Goodne...

24 Jan 201822min

Solving Imperfect-Information Games with Tuomas Sandholm - NIPS ’17 Best Paper - TWiML Talk #99

Solving Imperfect-Information Games with Tuomas Sandholm - NIPS ’17 Best Paper - TWiML Talk #99

In this episode I speak with Tuomas Sandholm, Carnegie Mellon University Professor and Founder and CEO of startups Optimized Markets and Strategic Machine. Tuomas, along with his PhD student Noam Brow...

22 Jan 201827min

Separating Vocals in Recorded Music at Spotify with Eric Humphrey - TWiML Talk #98

Separating Vocals in Recorded Music at Spotify with Eric Humphrey - TWiML Talk #98

In today’s show, I sit down with Eric Humphrey, Research Scientist in the music understanding group at Spotify. Eric was at the Deep Learning Summit to give a talk on Advances in Deep Architectures an...

19 Jan 201827min

Accelerating Deep Learning with Mixed Precision Arithmetic with Greg Diamos - TWiML Talk #97

Accelerating Deep Learning with Mixed Precision Arithmetic with Greg Diamos - TWiML Talk #97

In this show I speak with Greg Diamos, senior computer systems researcher at Baidu. Greg joined me before his talk at the Deep Learning Summit, where he spoke on “The Next Generation of AI Chips.” Gre...

17 Jan 201839min

Composing Graphical Models With Neural Networks with David Duvenaud - TWiML Talk #96

Composing Graphical Models With Neural Networks with David Duvenaud - TWiML Talk #96

In this episode, we hear from David Duvenaud, assistant professor in the Computer Science and Statistics departments at the University of Toronto. David joined me after his talk at the Deep Learning S...

15 Jan 201835min

Embedded Deep Learning at Deep Vision with Siddha Ganju - TWiML Talk #95

Embedded Deep Learning at Deep Vision with Siddha Ganju - TWiML Talk #95

In this episode we hear from Siddha Ganju, data scientist at computer vision startup Deep Vision. Siddha joined me at the AI Conference a while back to chat about the challenges of developing deep lea...

12 Jan 201834min

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