Data Science Now

So far in this series on Artificial Intelligence Artificial Intelligence: Monster or Mentor? and AI for Summarization – Enabling Human-Consumable Information, we looked at several key ways in which AI advances can improve human productivity in organizations. Last time’s article dove into Distillation – automating the path to value.

Predictive Analytics World, London, 11-12 October – Agenda is Live

The agenda for PAW London 2017 has just been released and we want you to be among the first to know what the hot topics will be this year.

[D] NIPS rebuttal period is open!

Thought this would be a nice place for people to discuss the rebuttal process / vent about reviews. I, for one, am curious how much this part of the process has mattered historical. How common is a reject review switched to an accept? Can a poor rebuttal lower review scores? submitted by /u/zergylord [link] [comments]

[D] Running an AI Startup and the Future of Deep NLP - Alex Lamb Interviews Daniel Jiwoong Im

submitted by /u/alexmlamb [link] [comments]

[R] [1707.06600] A multi-agent reinforcement learning model of common-pool resource appropriation

submitted by /u/enderwagon [link] [comments]

Summary of Unintuitive Properties of Neural Networks

These days neural networks have been working really well on language, image and speech recognition. However we need a global understanding of what a neural network is thinking anytime soon. There are several count-intuitive properties of neural network discussed in this post.

When not to use deep learning

Despite DL many successes, there are at least 4 situations where it is more of a hindrance, including low-budget problems, or when explaining models and features to general public is required.

[N] CNTK + LSTM + kinect v2 = Face analysis

submitted by /u/pmfcdb [link] [comments]

[P] Intelligent Topic Detection with Unsupervised Learning

AI for Organizing – Categorizing and Managing Data at Scale