Real Time Trigger Word Detection with Keras
https://hackernoon.com/how-to-do-real-time-trigger-word-detection-with-keras-b8a56ab106b7
https://hackernoon.com/how-to-do-real-time-trigger-word-detection-with-keras-b8a56ab106b7
Hacker Noon
How to do Real Time Trigger Word Detection with Keras
I just finished the Coursera deep learning online program this week. The last programming assignment is about trigger word detection, aka…
Emotion AI и эмоциональные технологии: конференция Neurodata Lab и НИУ ИТМО
https://habrahabr.ru/company/neurodatalab/blog/350478/
https://habrahabr.ru/company/neurodatalab/blog/350478/
habrahabr.ru
Emotion AI и эмоциональные технологии: конференция Neurodata Lab и НИУ ИТМО
30 марта 2018 г. Neurodata Lab LLC и НИУ ИТМО проводят однодневную конференцию в Санкт-Петербурге (мероприятие в Москве также запланировано на ближайшее...
Implementation of AlphaZero for Gomoku (TensorFlow, Pytorch and Theano)
https://github.com/junxiaosong/AlphaZero_Gomoku
https://github.com/junxiaosong/AlphaZero_Gomoku
GitHub
GitHub - junxiaosong/AlphaZero_Gomoku: An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a…
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row) - GitHub - junxiaosong/AlphaZero_Gomoku: An implementation of the AlphaZero algorithm for Gomoku (also...
Tensor Comprehensions in PyTorch
https://pytorch.org/2018/03/05/tensor-comprehensions.html
https://pytorch.org/2018/03/05/tensor-comprehensions.html
Новое на Distill: The Building Blocks of Interpretability
https://distill.pub/2018/building-blocks/
https://distill.pub/2018/building-blocks/
Distill
The Building Blocks of Interpretability
Interpretability techniques are normally studied in isolation. We explore the powerful interfaces that arise when you combine them -- and the rich structure of this combinatorial space.
A collection of research directions around transfer learning and NLP
https://ruder.io/requests-for-research/
https://ruder.io/requests-for-research/
ruder.io
Requests for Research
It can be hard to find compelling topics to work on and know what questions to ask when you are just starting as a researcher. This post aims to provide inspiration and ideas for research directions to junior researchers and those trying to get into research.
Щи или распознавание 330 млн лиц на скорости 400 фото / сек
https://habrahabr.ru/company/odnoklassniki/blog/350566/
https://habrahabr.ru/company/odnoklassniki/blog/350566/
Habr
Щи, или Распознавание 330 млн лиц на скорости 400 фото / сек
Распознаванием лиц в 2018 году никого не удивишь – каждый студент, может, даже школьник, его делал. Но всё становится немного сложнее, когда у вас не датасет на 1 млн пользователей, а:
330...
330...
Первые шаги в Машинном обучении
https://habrahabr.ru/post/350984/
https://habrahabr.ru/post/350984/
Habr
Первые шаги в машинном обучении
Привет, дорогой друг, ты всегда хотел попробовать машинное обучение, но область выглядела загадочно и сложно? Я хотел бы поделиться с тобой моей историей как я сделал первые шаги в машинном обучении,...
Semantic Image Segmentation with DeepLab in Tensorflow
https://research.googleblog.com/2018/03/semantic-image-segmentation-with.html
https://research.googleblog.com/2018/03/semantic-image-segmentation-with.html
research.google
Semantic Image Segmentation with DeepLab in TensorFlow
Posted by Liang-Chieh Chen and Yukun Zhu, Software Engineers, Google ResearchSemantic image segmentation, the task of assigning a semantic label, s...
Weakly supervised learning of linear boundary
https://github.com/4d55397500/learning-scraps/tree/master/mitr
https://github.com/4d55397500/learning-scraps/tree/master/mitr
GitHub
4d55397500/learning-scraps
learning-scraps - low-level learning scraps
Plain python implementations of basic machine learning algorithms
https://github.com/zotroneneis/machine_learning_basics
https://github.com/zotroneneis/machine_learning_basics
GitHub
GitHub - zotroneneis/machine_learning_basics: Plain python implementations of basic machine learning algorithms
Plain python implementations of basic machine learning algorithms - zotroneneis/machine_learning_basics
Made a graph of nearest neighbors from word2vec embeddings. What do you think?
https://github.com/anvaka/word2vec-graph
https://github.com/anvaka/word2vec-graph
GitHub
GitHub - anvaka/word2vec-graph: Exploring word2vec embeddings as a graph of nearest neighbors
Exploring word2vec embeddings as a graph of nearest neighbors - anvaka/word2vec-graph
PyTorch Implementation of the "Magnet Loss": Metric Learning with Adaptive Density Discrimination from Facebook AI Research
https://github.com/vithursant/MagnetLoss-PyTorch
https://github.com/vithursant/MagnetLoss-PyTorch
GitHub
GitHub - vithursant/MagnetLoss-PyTorch: PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook…
PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016. - vithursant/MagnetLoss-PyTorch
Implementation of "Independently Recurrent Neural Network (IndRNN)" in TensorFlow
https://github.com/batzner/indrnn
https://github.com/batzner/indrnn
GitHub
GitHub - batzner/indrnn: TensorFlow implementation of Independently Recurrent Neural Networks
TensorFlow implementation of Independently Recurrent Neural Networks - batzner/indrnn
Pytorch implementation for Snapshot Ensemble with SGDR
https://jsideas.net/python/2018/03/14/snapshot_ensemble.html
https://jsideas.net/python/2018/03/14/snapshot_ensemble.html