Kaggle:[資料分析&機器學習] 第1.3講:Kaggle介紹. ...

[資料分析&機器學習] 第1.3講:Kaggle介紹. ...

[資料分析&機器學習] 第1.3講:Kaggle介紹. ...

2017年9月22日—Kaggle是全世界公認最大的資料科學社群,在Kaggle上隨時都有各種資料分析的比賽正在進行,由於這些比賽都會提供高額的獎金,因此會吸引全世界優秀的 ...。其他文章還包含有:「Kaggle」、「Kaggle」、「FindOpenDatasetsandMachineLearningProjects」、「LearnPython,DataViz」、「RunDataScience&MachineLearningCodeOnline」、「LearnPython」、「Competitions」

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Kaggle是全世界公認最大的資料科學社群,在Kaggle上隨時都有各種資料分析的比賽正在進行,由於這些比賽都會提供高額的獎金,因此會吸引全世界優秀的資料科學家前來比賽,並有許多熱愛分享的科學家在比賽過後再討論區留下他們的當初思考問題的邏輯以及解題的脈絡,研讀上面的討論串對於提升自己各方面的思考能力有很大的幫助。其他類似的網站像是KDDcup,中國的天池、DataCastle、DataFountain。在Kaggle上面的比賽有分不同的類別,對於剛入門的初學者來說,上面很多比賽並不是那麼的適合,比如說有些比賽光是資料集就30–40GB,對於一般...

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Kaggle
Kaggle

https://www.kaggle.com

Kaggle is the world's largest data science community with powerful tools and resources to help you achieve your data science goals.

Provide From Google
Kaggle
Kaggle

https://zh.wikipedia.org

Kaggle是一個數據建模和數據分析競賽平台。企業和研究者可在其上發布數據,統計學者和數據挖掘專家可在其上進行競賽以產生最好的模型。這一眾包模式依賴於這一事實,即 ...

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Find Open Datasets and Machine Learning Projects
Find Open Datasets and Machine Learning Projects

https://www.kaggle.com

Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More.

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Learn Python, Data Viz
Learn Python, Data Viz

https://www.kaggle.com

Kaggle Competitions are machine learning challenges, often with large prizes. Natural Language Processing Guide. NLP is a subfield of ML concerned with ...

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Run Data Science & Machine Learning Code Online
Run Data Science & Machine Learning Code Online

https://www.kaggle.com

Kaggle Notebooks are a computational environment that enables reproducible and collaborative analysis.

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Learn Python
Learn Python

https://www.kaggle.com

Kaggle. search. Sign In · Register. Got it. Learn more. Python. Learn the most important language for data science. 5 hours to go. Begin Course. Courses.

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Competitions
Competitions

https://www.kaggle.com

Kaggle is the world's largest data science community with powerful tools and resources to help you achieve your data science goals.

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