Productizing ML at Scale at Twitter with Yi Zhuang - TWIML Talk #271

This article summarizes a podcast episode discussing the implementation of Machine Learning (ML) at Twitter. It highlights key aspects such as the history of the Cortex team, the Deepbird v2 platform for model training and evaluation, and the newly formed "Meta" team focused on bias, fairness, and accountability in ML models. The conversation likely delves into the challenges and strategies of scaling ML within a large organization like Twitter, providing insights into their infrastructure and approach to responsible AI development.

• •Twitter's ML landscape and the role of the Cortex team.
• •The use of Deepbird v2 for model training and evaluation, including its integration with TensorFlow 2.0.
• •The formation of the "Meta" team to address bias, fairness, and accountability in ML models.