Advancing Hands-On Machine Learning Education with Sebastian Raschka - #565

Advancing Hands-On Machine Learning Education with Sebastian Raschka - #565

Today we’re joined by Sebastian Raschka, an assistant professor at the University of Wisconsin-Madison and lead AI educator at Grid.ai. In our conversation with Sebastian, we explore his work around AI education, including the “hands-on” philosophy that he takes when building these courses, his recent book Machine Learning with PyTorch and Scikit-Learn, his advise to beginners in the field when they’re trying to choose tools and frameworks, and more. We also discuss his work on Pytorch Lightning, a platform that allows users to organize their code and integrate it into other technologies, before switching gears and discuss his recent research efforts around ordinal regression, including a ton of great references that we’ll link on the show notes page below! The complete show notes for this episode can be found at twimlai.com/go/565

Episoder(766)

Acoustic Word Embeddings for Low Resource Speech Processing with Herman Kamper - TWiML Talk #191

Acoustic Word Embeddings for Low Resource Speech Processing with Herman Kamper - TWiML Talk #191

In this episode of our Deep Learning Indaba Series, we’re joined by Herman Kamper, lecturer at Stellenbosch University in SA and a co-organizer of the Indaba. We discuss his work on limited- and zero-resource speech recognition, how those differ from regular speech recognition, and the tension between linguistic and statistical methods in this space. We also dive into the specifics of the methods being used and developed in Herman’s lab.

16 Okt 20181h 1min

Learning Representations for Visual Search with Naila Murray - TWiML Talk #190

Learning Representations for Visual Search with Naila Murray - TWiML Talk #190

In this episode of our Deep Learning Indaba series, we’re joined by Naila Murray, Senior Research Scientist and Group Lead in the computer vision group at Naver Labs Europe. Naila presented at the Indaba on computer vision. In this discussion, we explore her work on visual attention, including why visual attention is important and the trajectory of work in the field over time. We also discuss her paper  “Generalized Max Pooling,” and much more! For the complete show notes, visit twimlai.com/tal

12 Okt 201841min

Evaluating Model Explainability Methods with Sara Hooker - TWiML Talk #189

Evaluating Model Explainability Methods with Sara Hooker - TWiML Talk #189

In this, the first episode of the Deep Learning Indaba series, we’re joined by Sara Hooker, AI Resident at Google Brain. I spoke with Sara in the run-up to the Indaba about her work on interpretability in deep neural networks. We discuss what interpretability means and nuances like the distinction between interpreting model decisions vs model function. We also talk about the relationship between Google Brain and the rest of the Google AI landscape and the significance of the Google AI Lab in Accra, Ghana.

10 Okt 20181h 3min

Graph Analytic Systems with Zachary Hanif - TWiML Talk #188

Graph Analytic Systems with Zachary Hanif - TWiML Talk #188

In this, the final episode of our Strata Data Conference series, we’re joined by Zachary Hanif, Director of Machine Learning at Capital One’s Center for Machine Learning. We start our discussion with a look at the role of graph analytics in the ML toolkit, including some important application areas for graph-based systems. Zach gives us an overview of the different ways to implement graph analytics, including what he calls graphical processing engines which excel at handling large datasets, & much m

8 Okt 201854min

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 Okt 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 Okt 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 Sep 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 Sep 201840min

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