Prerequisites: This article assumes you are familiar with the basics of Python, TensorFlow, and Jupyter notebooks. We won't use any of the advanced TensorFlo...

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit - microsoft/CNTK

Artificial Intelligence in 2017

This is just a short note to highlight a new paper I read recently: Roth, Lucchi, Nowozin and Hofmann (2017) Stabilizing Training of Generative Adversarial Networks through Regularization Instance noise Last year, we and Arjovsky & Buttou (2017) independently…

🔮 A refreshing functional take on deep learning, compatible with your favorite libraries - explosion/thinc

PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation - jacobgil/pytorch-explain-black-box

WebDNN is an open source software framework for fast execution of deep neural network (DNN) pre-trained model on web browser.

Update Oct 18, 2017: AlphaGo Zero was announced. This post refers to the previous version. 95% of it still applies.

Как вычислить замыслы киберпреступников, атакующих промышленный объект и распознать слабые сигналы SOS, которые периодически подает индустриальная АСУ ТП на...

Перевод поста Филиппа Ходжетта, выступавшего недавно на конференции Hollywood Professional Association Tech Retreat. Надеюсь, собранный в одном месте список...

Изложение статьи от том, что давно известные эволюционные стратегии оптимизации могут превзойти алгоритмы обучения с подкреплением. Преимущества эволюционных...

Deep learning neural networks are very easy to create and evaluate in Python with Keras, but you must follow a strict model life-cycle.

In this post, you will discover the step-by-step life-cycle for creating, training, and evaluating Long Short-Term Memory…

An adversarial example library for constructing attacks, building defenses, and benchmarking both - cleverhans-lab/cleverhans

Code for "On the Effects of Batch and Weight Normalization in Generative Adversarial Networks" - stormraiser/GAN-weight-norm