Deep Reinforcement Learning Hands-On
by Maxim Lapan · first published 2018
3mentions
1recommended by
3HN commenters
2018–2023first – last mentioned
33% recommend67% neutral
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…Applications" by Richard Szeliski "Deep Learning for Computer Vision" by Adrian Rosebrock Reinforcement Learning: "Reinforcement Learning: An Introduction" by Richard S. Sutton and Andrew G. Barto "Deep Reinforcement Learning Hands-On" by Maxim Lapan Stage 4: Staying Current and Gaining Practical Experience Read research papers: Subscribe to the arXiv mailing list in your areas of interest Regularly read papers from conferences…
on “Ask HN: I am a full stack developer, where do I start learning for AI” ↗…say it depends on your use cases. If you want high level understanding then go with Melanie Mitchell's book. If you want more technical details then d2l.ai or fast.ai are good choices. There's also "Deep Reinforcement Learning Hands-On" by Maxim Lapan. That one is also pretty good but I'm not far enough along to give a review one way or another.
on “The Case for Bayesian Deep Learning” ↗I need to figure out how to turn this into an openAI gym so I can train my DQN on it. I just finished running the code from Deep Reinforcement Learning - Hands on for Pong, and it's pretty cool...
on “Show HN: Beat my tank through strategy and programming” ↗