目录 概 主要内容 Note Madry A, Makelov A, Schmidt L, et al. Towards Deep Learning Models Resistant to Adversarial Attacks.[J]. arXiv: Machine Learning, 2017. @article{madry2017towards, title={Towards Deep Learning Models Resistant to Adversarial Attacks.},…
Hyperparameter optimization is a big part of deep learning. The reason is that neural networks are notoriously difficult to configure and there are a lot of parameters that need to be set. On top of that, individual models can be very slow to train.…
w强化算法和数学,来迎接机器学习.神经网络. http://cs.stanford.edu/people/karpathy/convnetjs/ ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no comp…
People commonly tend to put much effort on hyperparameter tuning and training while using Tensoflow&Deep Learning. A realistic problem for TF is how to integrate models into industry: saving pre-trained models, restoring them when necessary, and doin…
What's the most effective way to get started with deep learning?       29 Answers     Yoshua Bengio, My lab has been one of the three that started the deep learning approach, back in 2006, along with Hinton's... Answered Jan 20, 2016   Originally Ans…
Awesome Deep Learning  Table of Contents Free Online Books Courses Videos and Lectures Papers Tutorials Researchers WebSites Datasets Frameworks Miscellaneous Contributing Free Online Books Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Cou…
HOME ABOUT CONTACT SUBSCRIBE VIA RSS   DEEP LEARNING FOR ENTERPRISE Distributed Deep Learning, Part 1: An Introduction to Distributed Training of Neural Networks Oct 3, 2016 3:00:00 AM / by Alex Black and Vyacheslav Kokorin Tweet inShare27   This pos…
The Brain vs Deep Learning Part I: Computational Complexity — Or Why the Singularity Is Nowhere Near July 27, 2015July 27, 2015 Tim Dettmers Deep Learning, NeuroscienceDeep Learning, dendritic spikes, high performance computing, neuroscience, singula…
Motivation: The lack of transparency of the deep  learning models creates key barriers to establishing trusts to the model or effectively troubleshooting classification errors Common methods on non-security applications: forward propagation / back pr…
声明:所有内容来自coursera,作为个人学习笔记记录在这里. Regularization Welcome to the second assignment of this week. Deep Learning models have so much flexibility and capacity that overfitting can be a serious problem, if the training dataset is not big enough. Sure it do…