The Machine Intelligence Behind Gboard
https://research.googleblog.com/2017/05/the-machine-intelligence-behind-gboard.html
https://research.googleblog.com/2017/05/the-machine-intelligence-behind-gboard.html
Research Blog
The Machine Intelligence Behind Gboard
Posted by Françoise Beaufays, Principal Scientist, Speech and Keyboard Team and Michael Riley, Principal Scientist, Speech and Languages Alg...
ICML 2017 Accepted Papers
https://2017.icml.cc/Conferences/2017/AcceptedPapersInitial
https://2017.icml.cc/Conferences/2017/AcceptedPapersInitial
Semi-supervised learning in python using pomegranate
https://github.com/jmschrei/pomegranate/blob/master/tutorials/Tutorial_8_Semisupervised_Learning.ipynb
https://github.com/jmschrei/pomegranate/blob/master/tutorials/Tutorial_8_Semisupervised_Learning.ipynb
GitHub
jmschrei/pomegranate
pomegranate - Fast, flexible and easy to use probabilistic modelling in Python.
Numerai’s New Tournament to Crowdsource the Future of the Stock Market
https://medium.com/numerai/numerais-new-tournament-to-crowdsource-the-future-of-the-stock-market-da1ac02adaef
https://medium.com/numerai/numerais-new-tournament-to-crowdsource-the-future-of-the-stock-market-da1ac02adaef
Medium
Numerai’s New Tournament to Crowdsource the Future of the Stock Market
The traditional crowdsourced machine learning tournament depends on a holdout dataset. The holdout data is some historical data known to…
Deep Voice 2: Multi-Speaker Neural Text-to-Speech
http://research.baidu.com/deep-voice-2-multi-speaker-neural-text-speech/
http://research.baidu.com/deep-voice-2-multi-speaker-neural-text-speech/
Everything that Works Works Because it's Bayesian: Why Deep Nets Generalize?
http://www.inference.vc/everything-that-works-works-because-its-bayesian-2/
http://www.inference.vc/everything-that-works-works-because-its-bayesian-2/
inFERENCe
Everything that Works Works Because it's Bayesian: Why Deep Nets Generalize?
The Bayesian community should really start going to ICLR. They really should
have started going years ago. Some people actually have.
For too long we Bayesians have, quite arrogantly, dismissed deep neural networks
as unprincipled, dumb black boxes that…
have started going years ago. Some people actually have.
For too long we Bayesians have, quite arrogantly, dismissed deep neural networks
as unprincipled, dumb black boxes that…
OpenAI Baselines: DQN
https://blog.openai.com/openai-baselines-dqn/
https://blog.openai.com/openai-baselines-dqn/
Intel открывает доступ к clDNN [высокопроизводительной библиотеке для глубокого обучения]
https://habrahabr.ru/company/1cloud/blog/329474/?utm_source=vk&utm_medium=social&utm_campaign=intel-otkryvaet-dostup-k-cldnn-%5Bvysokopr
https://habrahabr.ru/company/1cloud/blog/329474/?utm_source=vk&utm_medium=social&utm_campaign=intel-otkryvaet-dostup-k-cldnn-%5Bvysokopr
habrahabr.ru
Intel открывает доступ к clDNN [высокопроизводительной библиотеке для глубокого обучения]
Официальный репозиторий проекта был запущен буквально пару дней назад. Расскажем немного подробнее об этой новости и приведем полезные источники по теме. /...
A practical explanation of a Naive Bayes classifier
https://monkeylearn.com/blog/practical-explanation-naive-bayes-classifier/
https://monkeylearn.com/blog/practical-explanation-naive-bayes-classifier/
MonkeyLearn Blog
A practical explanation of a Naive Bayes classifier
Naive Bayes is a family of simple but powerful machine learning algorithms that use probabilities and Bayes’ Theorem to predict the category of a text.
NIPS 2016: A survey of tutorials, papers, and workshops
https://www.twosigma.com/insights/nips-2016-a-survey-of-tutorials-papers-and-workshops-two-sigma
https://www.twosigma.com/insights/nips-2016-a-survey-of-tutorials-papers-and-workshops-two-sigma
Two Sigma
NIPS 2016: A survey of tutorials, papers, and workshops | Two Sigma
Two Sigma researchers discuss notable advances in deep learning, optimization algorithms, Bayesian techniques, and time-series analysis presented at 2016's Conference on Neural Information Processing Systems (NIPS).
Using Empirical Bayes to approximate posteriors for large "black box" estimators
http://www.unofficialgoogledatascience.com/2015/11/using-empirical-bayes-to-approximate.html
http://www.unofficialgoogledatascience.com/2015/11/using-empirical-bayes-to-approximate.html
Unofficialgoogledatascience
Using Empirical Bayes to approximate posteriors for large "black box" estimators
by OMKAR MURALIDHARAN Many machine learning applications have some kind of regression at their core, so understanding large-scale regressi...
COMMON REPRESENTATION LEARNING USING DEEP CORRNET
https://deeplearn.school.blog/2017/05/24/common-representation-learning-using-deep-corrnet/
https://deeplearn.school.blog/2017/05/24/common-representation-learning-using-deep-corrnet/
Deep learn
Common Representation Learning using Deep CorrNet
In this post, I am going to discuss Deep CorrNet that is described in Correlational Neural Network which is a Common Representation Learning (CRL) technique. I have implemented CorrNet in Python us…
Machine Learning Basics: a Guide for the Perplexed
http://blog.aylien.com/machine-learning-basics-guide-perplexed/
http://blog.aylien.com/machine-learning-basics-guide-perplexed/
AYLIEN
Machine Learning Basics: a Guide for the Perplexed - AYLIEN
FacebookTwitterLinkedInArtificial Intelligence and Machine Learning play a bigger part in our lives today than most people can imagine. We use intelligent services and applications every day that rely heavily on Machine Learning advances. Voice activation…
Анализ рынка недвижимости методом случайного леса
https://habrahabr.ru/post/329504/
https://habrahabr.ru/post/329504/
habrahabr.ru
Анализ рынка недвижимости методом случайного леса
Решалась задача анализа текущих предложений на минском рынке недвижимости с целью поиска недооцененных квартир. В качестве источника информации был выбран сайт...
cs231n lecture from Stanford, comparing between TensorFlow and PyTorch
http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture8.pdf
http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture8.pdf
Hybrid Generative-Discriminative Deep Models
http://www.openias.org/hybrid-generative-discriminative
http://www.openias.org/hybrid-generative-discriminative
www.openias.org
OpenIAS | Hybrid Generative-Discriminative Deep Models
Deep discriminative classifiers perform remarkably well on problems witha lot of labeled data. So-called deep generative models tend to excel whenlabeled tra...
PyTorch Tutorial for Deep Learning Researchers
https://github.com/yunjey/pytorch-tutorial
https://github.com/yunjey/pytorch-tutorial
GitHub
GitHub - yunjey/pytorch-tutorial: PyTorch Tutorial for Deep Learning Researchers
PyTorch Tutorial for Deep Learning Researchers. Contribute to yunjey/pytorch-tutorial development by creating an account on GitHub.