The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Exploring TensorFlow 2.0 with Paige Bailey - TWiML Talk #242
Mar 25, 2019
In this discussion, Paige Bailey, a TensorFlow developer advocate at Google with a rich background in machine learning, shares insights on TensorFlow 2.0's alpha release. They delve into the evolution of TensorFlow APIs and highlight the benefits of eager execution and Keras integration. Paige emphasizes community collaboration and the significance of tools like tf.function. She also discusses her transformative journey in the field and the opportunities within programs like Google Summer of Code, fostering innovation in tech.
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Paige Bailey's Career Journey
- Paige Bailey's background is in geophysics and applied math, with research in planetary science.
- She transitioned into machine learning through data analysis at NASA and predictive modeling at Chevron.
Developer Advocacy at Google
- A Developer Advocate at Google focuses on improving user experience through various means.
- These include documentation, UX research, tutorials, and community engagement.
TensorFlow 2.0 Alpha Release
- TensorFlow 2.0 alpha focuses on ease of use, Keras integration, and eager execution.
- Eager execution simplifies debugging and provides a Pythonic experience.