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Напоминаем, что сегодня состоится встреча с Михаилом Цветковым, руководителем технической группы Intel в России.

Тема встречи - «Технологии Intel для машинного обучения и систем AI: новый процессинг, новая иерархия памяти и новый нейроморфный чип».

Начало семинара в 19:30 02 апреля в 105 БК.

Успейте зарегистрироваться на встречу до 12:00: vk.cc/7K2OpT

Рубрика «Читаем статьи за вас». Декабрь 2017 — Январь 2018
https://habrahabr.ru/company/ods/blog/352508/

Data Fest — это крупнейшая бесплатная конференция, объединяющая исследователей, инженеров и разработчиков, связанных с data science.
http://datafest.ru/

Five video classification methods in Keras and TensorFlow
https://blog.coast.ai/five-video-classification-methods-implemented-in-keras-and-tensorflow-99cad29cc0b5

mlpack 3.0 released: a fast, flexible machine learning library
http://www.mlpack.org/gsocblog/mlpack-3-released.html

The 2018 Stanford CS224n NLP course projects are now online. A lot of them are pretty impressive.
http://web.stanford.edu/class/cs224n/reports.html

Датасет для экспериментов с One Shot Learning в NLP https://www.kaggle.com/generall/oneshotwikilinks
Датасет на основе WikiLinks, представляет собой скрауленные ссылки на статьи в Wikipedia, т.е. предполагается решать задачу Named Entity Linking.

The Annotated Transformer: Line-by-Line PyTorch implementation of "Attention is All You Need"
http://nlp.seas.harvard.edu/2018/04/03/attention.html

Google Colaboratory: Automatic Tensorflow/Keras Checkpoints in your Google Drive
https://github.com/Zahlii/colab-tf-utils

Intro to XGBoost (detecting Parkinson's with XGBoost Classifiers)
https://medium.com/@priansh/detect-parkinsons-with-10-lines-of-code-intro-to-xgboost-51a4bf76b2e6

Материалы курса "Глубинное обучение", прочитанного на ФКН ВШЭ весной 2018г.
https://github.com/aosokin/DL_CSHSE_spring2018

Tsetlin Machine Python implementation
https://github.com/janvdvegt/tsetlin

Triplet Loss and Online Triplet Mining in TensorFlow
https://omoindrot.github.io/triplet-loss

Применение сверточных нейронных сетей для задач NLP
https://habrahabr.ru/company/ods/blog/353060/

A modular open-source image query dictionary app for Android using Tensorflow Lite (TFlite) and SQLite
https://github.com/queryChain/queryChain

Keras Learning Rate Finder (+ SGDR and CLR)
https://github.com/nathanhubens/Learning-Rate

How I monitor and track my machine learning experiments from anywhere (described in 13 tweets)
https://twitter.com/rememberlenny/status/983897644094447617

Implementations of 15 NLP research papers using Keras, Tensorflow, and Scikit Learn.
https://github.com/GauravBh1010tt/DeepLearn

Официальный резил тайга 2.0. Краткая выжимка, по ссылке более детально:
We have gathered the resources with respect to popular NLP-problems:

thematic modelling - news with theme tags, all the sites which provide rubrication (news, poems, prose)
readability of texts - a popular science magazine NPlus1 has a readability metric for each text, provided by editor.
NER and fact extraction - news with references to mentioned person’s page or wiki-information, news with personalia tags
key-words extraction - news with key-word tags, hashtags on social media
authorship attribution - all the texts with author information - magazines, news, and more important - social media - with gender, age, city, time and education mark-up.
chat-bot training - open-source film subnoscripts
text generation - any resource depending on genre
rare words studying, frequency dictionaries - literary magazines, social media
morphological and syntactic parsers - any resource with respect to the genre
Taiga corpus is an ambitious project to become the largest fully available webcorpus constructed from open text sources. Taiga corpus is:

open source, CC BY-SA 3.0
big - about 5 billion words by now
sorted by datasets applicable to different machine laearning tasks
made by linguists, experienced in text crawling, parsing and filtering
rich with metainformation
POS-tagged and syntactically tagged in Universal Dependencies
https://tatianashavrina.github.io/taiga_site/

Создатели:
Tatiana Shavrina (rybolos@gmail.com)
Yana Kurmachova (yana.kurmacheva@gmail.com)

Python module to easily generate text using a pretrained character-based recurrent neural network.
https://github.com/minimaxir/textgenrnn?reddit=1

Which of the Hollywood stars is most similar to my voice?
https://github.com/andabi/voice-vector