Chip Huyen — ML Research and Production Pipelines

Chip Huyen — ML Research and Production Pipelines

Chip Huyen is a writer and computer scientist currently working at a startup that focuses on machine learning production pipelines. Previously, she’s worked at NVIDIA, Netflix, and Primer. She helped launch Coc Coc - Vietnam’s second most popular web browser with 20+ million monthly active users. Before all of that, she was a best selling author and traveled the world. Chip graduated from Stanford, where she created and taught the course on TensorFlow for Deep Learning Research. Check out Chip's recent article on ML Tools: https://huyenchip.com/2020/06/22/mlops.html Follow Chip on Twitter: https://twitter.com/chipro And on her Website: https://huyenchip.com/ Visit our podcasts homepage for transcripts and more episodes! www.wandb.com/podcast 🔊 Get our podcast on Apple and Spotify! Apple Podcasts: https://bit.ly/2WdrUvI Spotify: https://bit.ly/2SqtadF We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast called Gradient Dissent. We hope you have as much fun listening to it as we had making it! 👩🏼‍🚀Weights and Biases: We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions. - Blog: https://www.wandb.com/articles - Gallery: See what you can create with W&B - https://app.wandb.ai/gallery - Continue the conversation on our slack community - http://bit.ly/wandb-forum 🎙Host: Lukas Biewald - https://twitter.com/l2k 👩🏼‍💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai 📹Editor: Cayla Sharp - http://caylasharp.com/

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Vicki Boykis — Machine Learning Across Industries

Vicki Boykis — Machine Learning Across Industries

👩‍💻Today our guest is Vicki Boykis! Vicki is a senior consultant in machine learning and engineering and works with clients to build holistic data products used for decision-making. She's previously...

4 Kesä 202034min

Angela & Danielle — Designing ML Models for Millions of Consumer Robots

Angela & Danielle — Designing ML Models for Millions of Consumer Robots

👩‍💻👩‍💻On this episode of Gradient Dissent our guests are Angela Bassa and Danielle Dean! Angela is an expert in building and leading data teams. An MIT-trained and Edelman-award-winning mathemati...

6 Touko 202052min

Jack Clark — Building Trustworthy AI Systems

Jack Clark — Building Trustworthy AI Systems

Jack Clark is the Strategy and Communications Director at OpenAI and formerly worked as the world’s only neural network reporter at Bloomberg. Lukas and Jack discuss AI policy, ethics, and the respons...

22 Huhti 202055min

Rachael Tatman — Conversational AI and Linguistics

Rachael Tatman — Conversational AI and Linguistics

🏅 See how W&B is your secret weapon to make it onto the Kaggle leaderboards - https://www.wandb.com/kaggle 👩‍💻Rachael Tatman is a developer advocate for Rasa, where she helps developers build and ...

7 Huhti 202036min

Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars

Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars

👨🏻‍💻Nicolas Koumchatzky is the Director of AI infrastructure at NVIDIA, where he's responsible for MagLev, the production-grade machine learning platform by NVIDIA. His team supports diverse ML use...

21 Maalis 202044min

Brandon Rohrer — Machine Learning in Production for Robots

Brandon Rohrer — Machine Learning in Production for Robots

👨🏻‍💻Brandon Rohrer is a Mechanical Engineer turned Data Scientist. He’s currently a Principal Data Scientist at iRobot and has an incredibly popular Machine Learning course at e2eML where he’s made...

11 Maalis 202034min

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