ML on code, Understanding RNNs, Deep Latent Variable Models, Writing Code for NLP Research, Quo vadis, NLP?, Democratizing AI, ML Cheatsheets, Spinning Up in Deep RL, Papers with Code, Unsupervised MT, Multilingual BERT, Graph Networks, AutoML
ML on code, Understanding RNNs, Deep Latent Variable Models, Writing Code for NLP Research, Quo vadis, NLP?, Democratizing AI, ML Cheatsheets, Spinning Up in Deep RL, Papers with Code, Unsupervised MT, Multilingual BERT, Graph Networks, AutoML
newsletter.ruder.io
Hey all,Welcome to this month’s newsletter edition! There's a lot of cool stuff this time, so better take a break and enjoy this edition with your beverage of choice ☕️🍵🍺🍹. The content includes talks by Stephen Wolfram and Greg Brockman; slides about ML on code, understanding RNNs, deep latent variable models, writing code for NLP research, transfer learning, and how to write good reviews; my take on what's next for NLP; content on democratizing AI; ML cheatsheets, Deep RL resources, and Papers with Code; implementations of unsupervised MT, multilingual BERT, RL libraries by Facebook and Google, Graph networks, and AutoML; and as always lots of cool articles, news, and papers.I really appreciate your feedback, so let me know what you love ❤️ and hate 💔 about this edition. Simply hit reply on the issue.If you were referred by a friend, click here to subscribe. If you enjoyed this issue, give it a tweet 🐦.
ML on code, Understanding RNNs, Deep Latent Variable Models, Writing Code for NLP Research, Quo vadis, NLP?, Democratizing AI, ML Cheatsheets, Spinning Up in Deep RL, Papers with Code, Unsupervised MT, Multilingual BERT, Graph Networks, AutoML
ML on code, Understanding RNNs, Deep Latent…
ML on code, Understanding RNNs, Deep Latent Variable Models, Writing Code for NLP Research, Quo vadis, NLP?, Democratizing AI, ML Cheatsheets, Spinning Up in Deep RL, Papers with Code, Unsupervised MT, Multilingual BERT, Graph Networks, AutoML
Hey all,Welcome to this month’s newsletter edition! There's a lot of cool stuff this time, so better take a break and enjoy this edition with your beverage of choice ☕️🍵🍺🍹. The content includes talks by Stephen Wolfram and Greg Brockman; slides about ML on code, understanding RNNs, deep latent variable models, writing code for NLP research, transfer learning, and how to write good reviews; my take on what's next for NLP; content on democratizing AI; ML cheatsheets, Deep RL resources, and Papers with Code; implementations of unsupervised MT, multilingual BERT, RL libraries by Facebook and Google, Graph networks, and AutoML; and as always lots of cool articles, news, and papers.I really appreciate your feedback, so let me know what you love ❤️ and hate 💔 about this edition. Simply hit reply on the issue.If you were referred by a friend, click here to subscribe. If you enjoyed this issue, give it a tweet 🐦.