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데이터 어디서구할 것인가?

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data.world/promptcloud/fashion-products-on-amazon-com#

 

Fashion products on Amazon.com - dataset by promptcloud

Dataset of 22,000 fashion products on Amazon

data.world

- 데이터량이 그렇게 많지는 않은데 (약 1만건 언저리) 나쁘지않다...!

research.google/tools/datasets/

 

Datasets – Google Research

Browse our library of open source projects, public datasets, APIs and more to find the tools you need to tackle your next challenge or fuel your next breakthrough.

research.google

구글에서 오픈한 데이터셋인데 내가찾는 자료는없다... 약간 standard 한 이쁜 데이터만 많은 듯 

 

codereview.stackexchange.com/questions/208277/web-scraping-google-trends-in-python

 

Web scraping google trends in python

Question Recently I have tried to create a web scraping program to get data from google trends. It uses an RSS feed to do so. My question is as follows: How can I improve my code such that it is ...

codereview.stackexchange.com

구글트렌드 크롤링하는 코드 

it really works with any hesitancy but,,,, 

medium.com/quick-code/python-scrapy-tutorial-for-beginners-04-crawler-rules-and-linkextractor-7a79aeb8d72

 

Python Scrapy tutorial for beginners — 04 — Crawler, Rules and LinkExtractor

In our last lesson, How to go to the next page, we scraped the whole website up to the last book. But today, we are going to learn a tool…

medium.com

크롤러만들기.. 아직돌려보진 않았다.

colah.github.io/posts/2015-08-Understanding-LSTMs/

 

Understanding LSTM Networks -- colah's blog

Posted on August 27, 2015 Humans don’t start their thinking from scratch every second. As you read this essay, you understand each word based on your understanding of previous words. You don’t throw everything away and start thinking

colah.github.io

LSTM 개념설명

 

점프투파이썬

wikidocs.net/26

구글의 페이지랭크 수학적원리

icim.nims.re.kr/post/easyMath/837

 

구글의 페이지랭크(PageRank) | 알기 쉬운 산업수학 | 산업수학혁신센터

 

icim.nims.re.kr

activation function관련 잘 정리된글 (LSTM tanh -> arctanh 구분효과)

reniew.github.io/12/

 

딥러닝에서 사용하는 활성화함수

An Ed edition

reniew.github.io

 

LSTM tanh

popularity based text prediction

fashion terms

how to extract the vocabulary from tokenizer python

word valuation based text generator

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