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.

Jaksot(778)

Diversification in Recommender Systems with Ahsan Ashraf - TWiML Talk #187

Diversification in Recommender Systems with Ahsan Ashraf - TWiML Talk #187

In this episode of our Strata Data conference series, we’re joined by Ahsan Ashraf, data scientist at Pinterest. We discuss his presentation, “Diversification in recommender systems: Using topical variety to increase user satisfaction,” covering the experiments his team ran to explore the impact of diversification in user’s boards, the methodology his team used to incorporate variety into the Pinterest recommendation system and much more! The show notes can be found at https://twimlai.com/talk/18

4 Loka 201844min

The Fastai v1 Deep Learning Framework with Jeremy Howard - TWiML Talk #186

The Fastai v1 Deep Learning Framework with Jeremy Howard - TWiML Talk #186

In today's episode we're presenting a special conversation with Jeremy Howard, founder and researcher at Fast.ai. This episode is being released today in conjunction with the company’s announcement of version 1.0 of their fastai library at the inaugural Pytorch Devcon in San Francisco. In our conversation, we dive into the new library, exploring why it’s important and what’s changed, the unique way in which it was developed, what it means for the future of the fast.ai courses, and much more!

2 Loka 20181h 11min

Federated ML for Edge Applications with Justin Norman - TWiML Talk #185

Federated ML for Edge Applications with Justin Norman - TWiML Talk #185

In this episode we’re joined by Justin Norman, Director of Research and Data Science Services at Cloudera Fast Forward Labs. In my chat with Justin we start with an update on the company before diving into a look at some of recent and upcoming research projects. Specifically, we discuss their recent report on Multi-Task Learning and their upcoming research into Federated Machine Learning for AI at the edge. For the complete show notes, visit https://twimlai.com/talk/185.

27 Syys 201847min

Exploring Dark Energy & Star Formation w/ ML with Viviana Acquaviva - TWiML Talk #184

Exploring Dark Energy & Star Formation w/ ML with Viviana Acquaviva - TWiML Talk #184

In today’s episode of our Strata Data series, we’re joined by Viviana Acquaviva, Associate Professor at City Tech, the New York City College of Technology. In our conversation, we discuss an ongoing project she’s a part of called the “Hobby-Eberly Telescope Dark Energy eXperiment,” her motivation for undertaking this project, how she gets her data, the models she uses, and how she evaluates their performance. The complete show notes can be found at https://twimlai.com/talk/184.

26 Syys 201840min

Document Vectors in the Wild with James Dreiss - TWiML Talk #183

Document Vectors in the Wild with James Dreiss - TWiML Talk #183

In this episode of our Strata Data series we’re joined by James Dreiss, Senior Data Scientist at international news syndicate Reuters. James and I sat down to discuss his talk from the conference “Document vectors in the wild, building a content recommendation system,” in which he details how Reuters implemented document vectors to recommend content to users of their new “infinite scroll” page layout.

24 Syys 201840min

Applied Machine Learning for Publishers with Naveed Ahmad - TWiML Talk #182

Applied Machine Learning for Publishers with Naveed Ahmad - TWiML Talk #182

In today’s episode we’re joined by Naveed Ahmad, Senior Director of data engineering and machine learning at Hearst Newspapers. In our conversation, we discuss into the role of ML at Hearst, including their motivations for implementing it and some of their early projects, the challenges of data acquisition within a large organization, and the benefits they enjoy from using Google’s BigQuery as their data warehouse. For the complete show notes for this episode, visit https://twimlai.com/talk/182.

20 Syys 201839min

Anticipating Superintelligence with Nick Bostrom - TWiML Talk #181

Anticipating Superintelligence with Nick Bostrom - TWiML Talk #181

In this episode, we’re joined by Nick Bostrom, professor at the University of Oxford and head of the Future of Humanity Institute, a multidisciplinary institute focused on answering big-picture questions for humanity with regards to AI safety and ethics. In our conversation, we discuss the risks associated with Artificial General Intelligence, advanced AI systems Nick refers to as superintelligence, openness in AI development and more! The notes for this episode can be found at https://twimlai.com/talk/18

17 Syys 201844min

Can We Train an AI to Understand Body Language? with Hanbyul Joo - TWIML Talk #180

Can We Train an AI to Understand Body Language? with Hanbyul Joo - TWIML Talk #180

In this episode, we’re joined by Hanbyul Joo, a PhD student at CMU. Han is working on what is called the “Panoptic Studio,” a multi-dimension motion capture studio used to capture human body behavior and body language. His work focuses on understanding how humans interact and behave so that we can teach AI-based systems to react to humans more naturally. We also discuss his CVPR best student paper award winner “Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies.”

13 Syys 201851min

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