ArtificialIntelligenceArticles
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for who have a passion for -
1. #ArtificialIntelligence
2. Machine Learning
3. Deep Learning
4. #DataScience
5. #Neuroscience

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Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers

Blog
https://fredhohman.com/visual-analytics-in-deep-learning/
Paper
arxiv.org/abs/1801.06889
Variational Bayesian Monte Carlo

: https://arxiv.org/abs/1810.05558
Quantum computers tackle big data with machine learning
https://www.nature.com/articles/s41467-018-06598-z @ArtificialIntelligenceArticles
Astrocytes integrate and drive action potential firing in inhibitory subnetworks

Deemyad et al.: https://www.nature.com/articles/s41467-018-06338-3 #brain #neuralnetworks
Typescript + Machine Learning + simplicity = Kalimdor.js

The NPM package for general Machine Learning

https://itnext.io/typescript-machine-learning-simplicity-kalimdor-js-bb1ccadf0ad3
Martingale Functional Control variates via Deep Learning. https://arxiv.org/abs/1810.05094 @ArtificialIntelligenceArticles
New Deep Learning Techniques 2018
Daniel Rueckert: "Deep learning in medical imaging"
https://goo.gl/UwXTBm @ArtificialIntelligenceArticles
Machine Learning and Likelihood-Free Inference in Particle Physics video : https://goo.gl/cBuJLH @ArtificialIntelligenceArticles
"Mathematics for Machine Learning": drafts for all chapters are now available https://mml-book.github.io/ @ArtificialIntelligenceArticles
Machine Learning Papers with Code - A searchable site that links machine learning papers on ArXiv with code on GitHub
https://paperswithcode.com/ @ArtificialIntelligenceArticles
Ten Simple Rules for Reproducible Research in Jupyter Notebooks

Rule et al.: https://arxiv.org/abs/1810.08055

#100DaysOfMLCode #BigData #ComputerScience #DataScience #MachineLearning
A birds-eye view of optimization algorithms

By Fabian Pedregosa: https://fa.bianp.net/teaching/2018/eecs227at/
How machine learning helps cancer research
https://goo.gl/Hz6Mbc @ArtificialIntelligenceArticles
"Artificial Intelligence needs all of us."

TEDxSanFrancisco talk by Rachel Thomasl: https://www.youtube.com/watch?v=LqjP7O9SxOM

#artificialintelligence #deeplearning #machinelearning
ProMP: Proximal Meta-Policy Search

Builds on MAML, E-MAML and DiCE.

Rothfuss et al.: https://arxiv.org/pdf/1810.06784.pdf

Code: https://github.com/jonasrothfuss/promp