Need data for deep learning?
Skymind's articles have cat memes! And a very comprehensive guide on finding data for deep learning.
https://skymind.ai/wiki/data-for-deep-learning

Free #OpenSource Datasets to Train #DeepLearning Models

Great list of public datasets from Google, Microsoft, Academic Torrents, Github, SkyMind. https://goo.gl/pR2KxG

New book by Christopher Bishop et al.: Model-based Machine Learning

https://mbmlbook.com/ @ArtificialIntelligenceArticles

Cross-Entropy Loss Leads To Poor Margins

paper : https://openreview.net/forum?id=ByfbnsA9Km @ArtificialIntelligenceArticles

Neural Approaches to Conversational AI

Gao et al.: https://arxiv.org/abs/1809.08267

#computation #language #machinelearning

A Brief Introduction to Machine Learning for Engineers

By Osvaldo Simeone : https://arxiv.org/abs/1709.02840

#artificialintelligence #deeplearning #machinelearning @ArtificialIntelligenceArticles

There’s now a new (and final) version of Sutton’s Reinforcement learning book at
https://incompleteideas.net/book/the-book-2nd.html

#reinforcementlearning

PinSage: A new graph convolutional neural network for web-scale recommender systems https://medium.com/@Pinterest_Engineering/pinsage-a-new-graph-convolutional-neural-network-for-web-scale-recommender

Open Source reimplementation of the Wolfram Research language in #Python.
Symbolic math, interactive 3D plots & accessible docs:
https://mybinder.org/v2/gh/wolfv/Mathics/binder?urlpath=proxy%2F1234%2F

Demis Hassabis : creativity and AI

The Rothschild Foundation Lecture : https://youtu.be/d-bvsJWmqlc

#artificialintelligence #creativity #reinforcementlearning

Q-map : a Convolutional Approach for Goal-Oriented Reinforcement Learning

Videos and code: https://sites.google.com/view/q-map-rl

paper : https://arxiv.org/abs/1810.02927

#artificialintelligence #machinelearning #reinforcementlearning

Training Neural Nets on Larger Batches: Practical Tips on 1-GPU, Multi-GPU & Distributed setups

link : https://goo.gl/tyVdGh #artificialintelligence #deeplearning @ArtificialIntelligenceArticles

The new fast.ai research datasets collection, on AWS Open Data
https://www.fast.ai/2018/10/16/aws-datasets/ @ArtificialIntelligenceArticles

Machine Learning for Physicists
https://www.video.uni-erlangen.de/course/id/574.html @ArtificialIntelligenceArticles

Large-Scale Study of Curiosity-Driven Learning

Burda et al.: https://pathak22.github.io/large-scale-curiosity/

CURIOUS: Intrinsically Motivated Multi-Task, Multi-Goal Reinforcement Learning

Colas et al.: https://arxiv.org/abs/1810.06284

the Most Important Machine Learning Books
The list of books that you should buy (and read) to become an expert in Machine Learning https://semanti.ca/blog/?the-most-important-machine-learning-books

Open sourcing TRFL : a library of reinforcement learning building blocks

Blog : https://deepmind.com/blog/trfl/
GitHub: https://github.com/deepmind/trfl/

#artificialintelligence #deeplearning

NVIDIA GPUs htop like monitoring tool

GitHub : https://github.com/Syllo/nvtop

#artificialintelligence #deeplearning #machinelearning

Generation meets recommendation: proposing novel items for groups of users

Vinh Vo et al. : https://dl.acm.org/citation.cfm?doid=3240323.3240357