Linking pages
- Super Intelligence for The Stock Market | by Richard Craib | Numerai | Medium https://medium.com/@Numerai/invisible-super-intelligence-for-the-stock-market-3c64b57b244c#.aivgp79ju 29 comments
- Deep-Learning-Papers-Reading-Roadmap/README.md at master · floodsung/Deep-Learning-Papers-Reading-Roadmap · GitHub https://github.com/songrotek/deep-learning-papers-reading-roadmap 29 comments
- Introduction to Autoencoders – P. Galeone's blog https://pgaleone.eu/neural-networks/2016/11/18/introduction-to-autoencoders/ 8 comments
- GitHub - jrdi/dl-glossary: The Open Source Deep Learning Glossary https://github.com/jrdi/dl-glossary 6 comments
- Adventures in Narrated Reality. New forms & interfaces for written… | by Ross Goodwin | Artists + Machine Intelligence | Medium https://medium.com/@rossgoodwin/adventures-in-narrated-reality-6516ff395ba3#.ew48b9qgw 5 comments
- GitHub - floodsung/Deep-Learning-Papers-Reading-Roadmap: Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech! https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap 5 comments
- How We Use Deep Learning to Classify Business Photos at Yelp http://engineeringblog.yelp.com/2015/10/how-we-use-deep-learning-to-classify-business-photos-at-yelp.html 4 comments
- Dropout and the Deep Complexity of Neural Networks https://rcoh.me/posts/dropout-deep-complexity/ 3 comments
- Fast CNN Tuning with AWS GPU Instances and SigOpt | AWS Machine Learning Blog https://aws.amazon.com/blogs/ai/fast-cnn-tuning-with-aws-gpu-instances-and-sigopt/ 1 comment
- Adding Noise to Regression Predictors is Ridge Regression http://madrury.github.io/jekyll/update/statistics/2017/08/12/noisy-regression.html 0 comments
- The Last 5 Years In Deep Learning – Adit Deshpande – Engineering at Forward | UCLA CS '19 https://adeshpande3.github.io/The-Last-5-Years-in-Deep-Learning 0 comments
- TensorFlow 1.0 is here. Let’s do some Deep Learning on the Amazon Cloud! | by Mariusz Kierski | Medium https://medium.com/sigmoidal/tensorflow-1-0-is-here-lets-do-some-deep-learning-on-the-amazon-cloud-9234eab31fa5 0 comments
- 50 things I learned at NIPS 2016. I learned many things about AI and ML… | by Andreas Stuhlmüller | Ought https://blog.ought.com/nips-2016-875bb8fadb8c#.yi31mk72p 0 comments
- Working with Fashion Models | Lyst Engineering Blog https://making.lyst.com/2017/02/21/working-with-fashion-models/ 0 comments
- GitHub - joanbruna/stat212b: Topics Course on Deep Learning UC Berkeley https://github.com/joanbruna/stat212b 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
- How to train your Deep Neural Network – Rishabh Shukla http://rishy.github.io/ml/2017/01/05/how-to-train-your-dnn/ 0 comments