Measuring Dataset Granularity. https://arxiv.org/abs/1912.10154

Exercism

Code practice and mentorship for everyone!

Level up your programming skills with 2,659 exercises across 48 languages, and insightful discussion with our dedicated team of welcoming mentors. Exercism is 100% free forever.

https://exercism.io/

Want to practice coding for interviews at a company like Google? May I recommend: https://rosalind.info/problems/list-view/, https://projecteuler.net, and https://exercism.io.

Facebook has a neural network that can do advanced math
https://www.technologyreview.com/s/614929/facebook-has-a-neural-network-that-can-do-advanced-math/#

A new deep learning algorithm can predict those at risk of psychosis with 93% accuracy by examining the latent semantic content of an individual’s speech.

https://neurosciencenews.com/ai-psychosis-words-14236/

Here's the original article if you want to know what it actually says. https://www.nature.com/articles/s41537-019-0077-9

MIT lecture series on deep learning in 2019
MIT lecture series on deep learning:Basics: https://www.youtube.com/watch?v=O5xeyoRL95U&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

MIT lecture series on deep learning: State of the Art:https://www.youtube.com/watch?v=53YvP6gdD7U&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

MIT lecture series on deep learning: Introduction to Deep RL: https://www.youtube.com/watch?v=zR11FLZ-O9M&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

Find The Most Updated and Free Artificial Intelligence, Machine Learning, Data Science, Deep Learning, Mathematics, Python Programming Resources
https://www.marktechpost.com/free-resources/

Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
Grathwohl et al.: https://arxiv.org/abs/1912.03263
#ArtificialIntelligence #DeepLearning #MachineLearning

“AI: Monte Carlo Tree Search (MCTS)”

de Pedro Torres Perez

https://rsci.app.link/LczXR6YnO2?_p=c11731dc9a0660eee31c8de3e9b6b9

CS 188 : Introduction to Artificial Intelligence
Pieter Abbeel & Dan Klein, University of California, Berkeley : https://inst.eecs.berkeley.edu/~cs188/fa18/
#ArtificialIntelligence #DeepLearning #ReinforcementLearning

Hierarchical Graph Pooling with Structure Learning
Zhang et al.: https://arxiv.org/abs/1911.05954
#ArtificialIntelligence #Graph #NeuralNetworks

BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
White et al.: https://arxiv.org/abs/1910.11858
#Bayesian #Optimization #NeuralArchitectureSearch

A Recipe for Training Neural Networks : [Andrej Karpathy blog](https://karpathy.github.io/)

[https://karpathy.github.io/2019/04/25/recipe/](https://karpathy.github.io/2019/04/25/recipe/)

Generating Interactive Worlds with Text
we present a machine learning (ML) approach to creating a cohesive and interesting world built from elements of the text-based fantasy game
ML models were trained to play the game by mimicking the actions and dialogues of human players in fixed settings built by crowd-workers.
In contrast, in this work, we study models for assembling the game itself rather than agents that play it
Paper:
https://arxiv.org/pdf/1911.09194.pdf

On the Morality of Artificial Intelligence
Alexandra Luccioni, Yoshua Bengio : https://arxiv.org/abs/1912.11945
#Society #AIEthics #ArtificialIntelligence

"Finally, machine learning interprets gene regulation clearly"
By Brian Stallard, Cold Spring Harbor Laboratory : https://phys.org/news/2019-12-machine-gene.html
#ArtificialIntelligence #Genetics #MachineLearning

"Differentiable Convex Optimization Layers"
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019

deeptraffic: DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series. https://github.com/lexfridman/deeptraffic

"Optuna: A Next-generation Hyperparameter Optimization Framework"
Akiba et al.: https://arxiv.org/abs/1907.10902
#ArtificialIntelligence #DataScience #MachineLearning