TensorFlow and Kubernetes
The conversation highlights the synergy between TensorFlow and Kubernetes, emphasizing their compatibility for distributed computing. While TensorFlow supports running across multiple machines and cores, many users stick with established Hadoop or Spark clusters due to their fault tolerance. The discussion raises the question of whether fault tolerance is truly necessary for machine learning tasks, given the typically long training durations.In this clip
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Video Object Detection at Scale with Reza Zadeh - #34
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