Ray talk

deanwampler · Jul 5, 2020 · a2efc50 · a2efc50
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diff --git a/Ray/Cluster-wide Scaling of ML with Ray.key b/Ray/Cluster-wide Scaling of ML with Ray.key
diff --git a/Ray/Cluster-wide Scaling of ML with Ray.pdf b/Ray/Cluster-wide Scaling of ML with Ray.pdf
diff --git a/Ray/image-credits.md b/Ray/image-credits.md
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+List of courses for example reinforcement learning images:
+
+* Games:
+	* DeepMind’s (Google’s) AlphaGo, released in 2016, which famously beat the 18-time world champion, Lee Sedol, in the game of Go, photo credit: https://www.geekwire.com/2016/alphago-ai-program-wins-1-million-prize-go-showdown-champion-lee-sedol/
+	* Atari breakout was an earlier achievement, photo credit: https://towardsdatascience.com/tutorial-double-deep-q-learning-with-dueling-network-architectures-4c1b3fb7f756
+* Robotics and autonomous vehicles: simulated locomotion, real-world robotic manipulation, mobility, pick and place, photo credits: unknown
+* Industrial control: We can teach a policy to optimize datacenter cooling and its energy consumption, factory floors. Ford assembly line photo credit: https://media.ford.com/content/fordmedia/fna/us/en/features/game-changer--100th-anniversary-of-the-moving-assembly-line.html)
+* System optimization: optimize database queries, cooling.
+	* Google datacenter photo: https://www.blog.google/inside-google/infrastructure/better-data-centers-through-machine/
+	* patch cabling photo: flickr.com/photos/jerryjohn
+* Advertising, recommendations. Video recommendations on YouTube diagram: https://research.google/pubs/pub45530/
+* Finance. photo credit: http://tradinghub.co/watch-list-for-mar-26th-2015/