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2014_02_statlearning_r

2014_04_getting-and-cleaning-data

2014_04_Getting and Cleaning Data

2014_09_algoritms_p1

by Kevin Wayne, Robert Sedgewick

2015_03_practicalmachinelearning

Home Work

algoritms

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

deep-learning-codebase

Codebase for fast prototyping of deep learning applications

deep-learning-for-recommendation-systems

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

dl_in_nlp_2019

Taking together Stanford cs224n course with support of iPavlov team.

dlpython_course

Примеры для курса "Программирование глубоких нейронных сетей на Python"

dsml_courses

Repository with my DSML Courses

home-credit-default-risk

2nd Place Solution 💰🥈

mashinnoye-obucheniye

:books: Специализация «Машинное обучение и анализ данных»

nlp_course

YSDA course in Natural Language Processing

notebooks

Machine learning notebooks in different subjects optimized to run in google collaboratory

practical_dl

DL course co-developed by YSDA, HSE and Skoltech

pwc

Papers with code. Sorted by stars. Updated weekly.

python_intro

Jupyter notebooks in Russian. Introduction to Python, basic algorithms and data structures

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

pytorch-openai-transformer-lm

A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI

pytorch-rnn-text-classification

Word Embedding + LSTM + FC

stanford_cs231n_2019

Solutions and comments to assignments for 2019 Stanford's course on convolutional neural networks

testrepository

tinkoff

tinkoff-boosters-2nd-place-

Решение первой задачи соревнования Tinkoff Data Science Challenge. Выложу только лучшую GBM модель из ансамбля, дает CV .7780, паблик примерно такой же. Остальные модели используют те же фичи и просто немного улучшают ансамбль

vvedenie-mashinnoe-obuchenie

:memo: Подборка ресурсов по машинному обучению