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1st_week

perl 1st week mail.ru

abae-pytorch

PyTorch implementation of 'An Unsupervised Neural Attention Model for Aspect Extraction' by He et al. ACL2017'

amazon-cell-phones-reviews

Scrape (un)locked cell phone ratings and reviews on Amazon

amazon-product-search-datasets

An benchmark dataset for personalized product search built on Amazon review data

amazon-reviews-analysis

Amazon Reviews Analysis

analytics_vidhya

Codes related to activities on AV including articles, hackathons and discussions.

apache_cluster

This repository is dedicated to installation and configuration cluster with Apache products

attention-based-aspect-extraction

Code for unsupervised aspect extraction, using Keras and its Backends

deeppavlov

An open source library for deep learning end-to-end dialog systems and chatbots.

deployml_course

Репозиторий для открытого курса «Промышленная эксплуатация моделей машинного обучения»

ec2-spot-labs

Collection of tools and code examples to demonstrate best practices in using Amazon EC2 Spot Instances.

hadoop-spark-standalone-docker

hse_spark_course

Репозиторий учебного материала для ДПО от ВШЭ (https://cs.hse.ru/dpo/). Курс Apache Spark

keras-contrib

Keras community contributions

mlcourse_open

Репозиторий открытого курса OpenDataScience по машинному обучению

music_library

ods_course_eng

python-kmedoids

Fast K-Medoids clustering in Python with FasterPAM

recom_way

seminars

speechkitcloud

Speechkit Cloud examples and SDK

sse-pt

Codes and Datasets for paper "Temporal Collaborative Ranking Via Personalized Transformer" and NurIPS'19 "Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers"

supernaive-kmedoids

A super naive implementation of k-medoids clustering algorithm

technosfera-perl

Техносфера "Программирование на perl"

tensorflow

An Open Source Machine Learning Framework for Everyone

test

test2

tutorials_and_presentations

There are all my tutorials and presentations from Python or Data Science events

week2

calculator

x5_retailhero_2020_recs

X5 Retailhero. 9 место решение задачи по рекомендациям