Variational Inference and Deep Learning: An Intuitive Introduction (by Alex Lamb)
https://www.youtube.com/watch?v=h0UE8FzdE8U
https://www.youtube.com/watch?v=h0UE8FzdE8U
YouTube
Variational Inference and Deep Learning: An Intuitive Introduction
A lecture introducing Variational Inference and Deep Learning. Adapted from a lecture I gave for Aaron Courville's Deep Learning course (IFT 6266).
Доклады с source{d} митапа про ML на исходном коде
https://www.youtube.com/playlist?list=PL5Ld68ole7j3iQFUSB3fR9122dHCUWXsy
https://www.youtube.com/playlist?list=PL5Ld68ole7j3iQFUSB3fR9122dHCUWXsy
YouTube
source{d} tech talks - Machine Learning 2017 - YouTube
Predicting Football Results With Statistical Modelling
https://dashee87.github.io/football/python/predicting-football-results-with-statistical-modelling/
https://dashee87.github.io/football/python/predicting-football-results-with-statistical-modelling/
dashee87.github.io
Predicting Football Results With Statistical Modelling
Combining the world’s most popular sport with everyone’s favourite discrete probability distribution, this post predicts football matches using the Poisson distribution.
Градиентный бустинг
https://alexanderdyakonov.wordpress.com/2017/06/09/%D0%B3%D1%80%D0%B0%D0%B4%D0%B8%D0%B5%D0%BD%D1%82%D0%BD%D1%8B%D0%B9-%D0%B1%D1%83%D1%81%D1%82%D0%B8%D0%BD%D0%B3/#more-5246
https://alexanderdyakonov.wordpress.com/2017/06/09/%D0%B3%D1%80%D0%B0%D0%B4%D0%B8%D0%B5%D0%BD%D1%82%D0%BD%D1%8B%D0%B9-%D0%B1%D1%83%D1%81%D1%82%D0%B8%D0%BD%D0%B3/#more-5246
Анализ малых данных
Градиентный бустинг
Пост про градиентный бустинг (Gradient Boosting), но не совсем обычный. Вместо текста прикрепляю pdf. Вопрос к читателям блога: будет ли полезно, если я подготовлю книжку в таком стиле по основным …
Playing a toy poker game with Reinforcement Learning
http://willtipton.com/coding/poker/2017/06/06/shove-fold-with-reinforcement-learning.html
http://willtipton.com/coding/poker/2017/06/06/shove-fold-with-reinforcement-learning.html
Willtipton
Playing a toy poker game with Reinforcement Learning
Coding and poker, mostly.
A DJ Khaled themed object recognizer app using inception v3, iOS CoreML and Vision
https://github.com/G2Jose/CoreMLVisionDJKhaled
https://github.com/G2Jose/CoreMLVisionDJKhaled
GitHub
G2Jose/CoreMLVisionDJKhaled
CoreMLVisionDJKhaled - Check if an object seen by your camera is a lion. Uses iOS CoreML, Vision APIs
MNIST FOR ML BEGINNERS: THE BAYESIAN WAY
https://alpha-i.co/blog/MNIST-for-ML-beginners-The-Bayesian-Way.html
https://alpha-i.co/blog/MNIST-for-ML-beginners-The-Bayesian-Way.html
CortexNet: a robust predictive deep neural network trained on videos
https://engineering.purdue.edu/elab/CortexNet/
https://engineering.purdue.edu/elab/CortexNet/
Google releases imagenet pre-trained mobilenet (faster/more-accurate than alexnet) models
https://research.googleblog.com/2017/06/mobilenets-open-source-models-for.html
https://research.googleblog.com/2017/06/mobilenets-open-source-models-for.html
research.google
MobileNets: Open-Source Models for Efficient On-Device Vision
Posted by Andrew G. Howard, Senior Software Engineer and Menglong Zhu, Software Engineer(Cross-posted on the Google Open Source Blog)Deep learning ...
Dropout — метод решения проблемы переобучения в нейронных сетях
https://habrahabr.ru/company/wunderfund/blog/330814/
https://habrahabr.ru/company/wunderfund/blog/330814/
Хабр
Dropout — метод решения проблемы переобучения в нейронных сетях
Переобучение (overfitting) — одна из проблем глубоких нейронных сетей (Deep Neural Networks, DNN), состоящая в следующем: модель хорошо объясняет только пример...
Один из самых значимых результатов в AI Safety (и не только) за последнее время, полученный при коллаборации исследователей из OpenAI и Deepmind.
https://blog.openai.com/deep-reinforcement-learning-from-human-preferences/
https://blog.openai.com/deep-reinforcement-learning-from-human-preferences/
OpenAI
Learning from Human Preferences
One step towards building safe AI systems is to remove the need for humans to
write goal functions, since using a simple proxy for a complex goal, or getting
the complex goal a bit wrong, can lead to undesirable and even dangerous
behavior [https://arxiv…
write goal functions, since using a simple proxy for a complex goal, or getting
the complex goal a bit wrong, can lead to undesirable and even dangerous
behavior [https://arxiv…
AgeHack — первый онлайн-хакатон по продлению жизни на платформе MLBootCamp
https://habrahabr.ru/company/mailru/blog/330960/
https://habrahabr.ru/company/mailru/blog/330960/
Хабр
AgeHack — первый онлайн-хакатон по продлению жизни на платформе MLBootCamp
Сегодня, 15 июня, стартует чемпионат на платформе ML Boot Camp, посвященный проблемам здравоохранения и долголетия человечества. Чемпионат организован нами совм...
Keras implementation of [A simple neural network module for relational reasoning]
https://github.com/Alan-Lee123/relation-network
https://github.com/Alan-Lee123/relation-network
GitHub
Alan-Lee123/relation-network
relation-network - keras implementation of [A simple neural network module for relational reasoning](https://arxiv.org/pdf/1706.01427.pdf)
PyTorch Implementation of "Principled Detection of Out-of-Distribution Examples in Neural Networks" (UIUC, Cornell)
https://github.com/shiyuliang/odin-pytorch
https://github.com/shiyuliang/odin-pytorch
GitHub
ShiyuLiang/odin-pytorch
odin-pytorch - Principled Detection of Out-of-Distribution Examples in Neural Networks
A TensorFlow Implementation of the Transformer: Attention Is All You Need
https://github.com/Kyubyong/transformer
https://github.com/Kyubyong/transformer
GitHub
GitHub - Kyubyong/transformer: A TensorFlow Implementation of the Transformer: Attention Is All You Need
A TensorFlow Implementation of the Transformer: Attention Is All You Need - Kyubyong/transformer
Phase-Functioned Neural Networks for Character Control
http://theorangeduck.com/page/phase-functioned-neural-networks-character-control
http://theorangeduck.com/page/phase-functioned-neural-networks-character-control
Theorangeduck
Phase-Functioned Neural Networks for Character Control
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