Hacker News
- Lessons Learned Reproducing a Deep Reinforcement Learning Paper (2018) http://amid.fish/reproducing-deep-rl 11 comments
- Lessons Learned Reproducing a Deep Reinforcement Learning Paper http://amid.fish/reproducing-deep-rl 22 comments
- "Lessons Learned Reproducing a Deep Reinforcement Learning Paper" over 8 months: DRL is hard; sweat the small stuff; keep records of changes; measure everything; use cloud to iterate faster; run repeatedly due to instability (Amid Fish) http://amid.fish/reproducing-deep-rl 3 comments reinforcementlearning
Linking pages
- ML engineering for AI safety & robustness: a Google Brain engineer's guide to entering the field - 80,000 Hours https://80000hours.org/articles/ml-engineering-career-transition-guide/ 66 comments
- GitHub - emilwallner/How-to-learn-Deep-Learning: A top-down, practical guide to learn AI, Deep learning and Machine Learning. https://github.com/emilwallner/How-to-learn-AI 1 comment
- GitHub - hadley/stats337: Readings in applied data science https://github.com/hadley/stats337 0 comments
- GitHub - adeshpande3/Machine-Learning-Links-And-Lessons-Learned: List of all the lessons learned, best practices, and links from my time studying machine learning https://github.com/adeshpande3/Machine-Learning-Links-And-Lessons-Learned 0 comments
- Machine Learning Productivity Hacks http://amid.fish/ml-productivity 0 comments
- AI at massive scale, and Reinforcement Learning in industry | by Emmanuel Ameisen | Insight https://blog.insightdatascience.com/ai-at-massive-scale-and-reinforcement-learning-in-industry-39d4a2c6ca26 0 comments
- DeepSuperLearner, Spherical CNNs, Google Semantris, Debater Data, AlterEgo, Text-to-Images GANs, Hate Speech Detection,… | by elvis | DAIR.AI | Medium https://medium.com/dair-ai/deepsuperlearner-spherical-cnns-google-semantris-debater-data-alterego-text-to-images-gans-2ba92eef9b9f 0 comments
Linked pages
- GitHub - dense-analysis/ale: Check syntax in Vim asynchronously and fix files, with Language Server Protocol (LSP) support https://github.com/w0rp/ale 261 comments
- Deep Reinforcement Learning Doesn't Work Yet https://www.alexirpan.com/2018/02/14/rl-hard.html 66 comments
- Google Colab https://colab.research.google.com/#scrollTo=Nma_JWh-W-IF 25 comments
- FloydHub Blog https://www.floydhub.com/ 25 comments
- Deep Reinforcement Learning: Pong from Pixels https://karpathy.github.io/2016/05/31/rl/ 16 comments
- Learning from Human Preferences https://blog.openai.com/deep-reinforcement-learning-from-human-preferences/ 7 comments
- OpenAI Scholars https://blog.openai.com/openai-scholars/ 1 comment
- http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html 0 comments
- GitHub - williamFalcon/DeepRLHacks: Hacks for training RL systems from John Schulman's lecture at Deep RL Bootcamp (Aug 2017) https://github.com/williamFalcon/DeepRLHacks 0 comments
- [1706.03741] Deep reinforcement learning from human preferences https://arxiv.org/abs/1706.03741 0 comments
- Distributed TensorFlow: A Gentle Introduction http://amid.fish/distributed-tensorflow-a-gentle-introduction 0 comments
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