R中的機器學習:通過並行計算加速模型構建



您是否想加快計算機器學習模型所需的時間? 在本視頻中,我向您展示了如何通過使用並行計算來加快模型構建。 ?給我買杯咖啡:https://www.buymeacoffee.com/dataprofessor⭕時間軸0:30啟動RStudio或RStudio.cloud 0:34從「數據教授」下載代碼GitHub 1:08打開dhfr-parallel-speed-up .R文件1:20 1.載入到DHFR數據集1:52 2.檢查缺失值1:56 3.設置可重現模型2:03的種子4.數據拆分為80/20子集2:28為我們的代碼計時4:22讓我們使用doParallel進行並行計算5:46並行計算會加速超參數調整嗎? 8:21結束語?數據:https://raw.githubusercontent.com/dataprofessor/data/master/dhfr.csv?CODE:https://github.com/dataprofessor/code/blob/master/dhfr/dhfr- ⭕播放列表:在以下播放列表中查看我們的其他視頻。 ✅數據科學101:https://bit.ly/dataprofessor-ds101✅數據科學YouTuber播客:https://bit.ly/datascience-youtuber-podcast✅數據科學虛擬實習:https://bit.ly/dataprofessor -internship✅生物信息學:http://bit.ly/dataprofessor-bioinformatics✅數據科學工具箱:https://bit.ly/dataprofessor-datasciencetoolbox✅Streamlit(Python中的網路應用):https://bit.ly/dataprofessor -streamlit✅閃亮(R中的Web應用程序):https://bit.ly/dataprofessor-shiny✅Google Colab提示和技巧:https://bit.ly/dataprofessor-google-colab✅熊貓提示和技巧:https: //bit.ly/dataprofessor-pandas✅Python數據科學項目:https://bit.ly/dataprofessor-python-ds✅R數據科學項目:https://bit.ly/dataprofessor-r-ds⭕訂閱:如果您是這裡的新手,那麼如果您考慮訂閱此頻道,對我來說就意味著世界。 ✅訂閱:https://www.youtube.com/dataprofessor?sub_confirmation=1⭕推薦工具:Kite是一款免費的AI驅動的編碼助手,可幫助您更快更智能地進行編碼。 Kite插件與所有頂級編輯器和IDE集成在一起,可在您鍵入時為您提供智能的補全和文檔。 我一直在使用風箏,我喜歡它! ✅查看風箏:https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=dataprofessor&utm_content=description-only⭕推薦書籍:✅使用Scikit-Learn的動手機器學習:https:// amzn.to/3hTKuTt from Scratch的數據科學:https://amzn.to/3fO0JiZ✅Python數據科學手冊:https://amzn.to/37Tvf8n✅R表示數據科學:https://amzn.to/2YCPcgW ✅人工智慧:哈佛商業評論需要的見解:https://amzn.to/33jTdcv✅人工智慧超級大國:中國,矽谷和新世界秩序:https://amzn.to/3nghGrd⭕庫存照片,此頻道上使用的圖形和視頻:✅https://1.envato.market/c/2346717/628379/4662⭕關注我們:✅媒介:http://bit.ly/chanin-medium✅FaceBook:http:/ /facebook.com/dataprofessor/✅網站:http://dataprofessor.org/(正在建設中)✅Twitter:https://twitter.com/thedataprof/✅Instagram:https://www.instagram.com/data。教授/✅LinkedIn:https://www.linkedin.com/in/chanin-nant asenamat /✅GitHub 1:https://github.com/dataprofessor/✅GitHub 2:https://github.com/chaninlab/⭕免責聲明:推薦的書籍和工具是會員鏈接,無償提供我一部分銷售給您,這將有助於改善此頻道的內容。 #dataprofessor#機器學習#並行計算#codespeed #fastcode #datascienceproject #learnr #rprogramming #learnrprogramming #datascience #datamining #bigdata #datascienceworkshop #dataminingworkshop #dataminingtutorial #datasciencetutorial #ai #artificialintelligence #r #doparallel。

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  1. ?QUESTION OF THE DAY: How much faster did this speed up your ML model building? Comments down below! ?
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  2. Questions: Is there any specific reason why you use number 5 as the argument of makePSOCKcluster? And is there any kind of maximum limit for this value? If so how can we know this maximum number? Last but not least… What is the definition of a cluster? Is it different from Core or CPU? Tensorflow also uses parallel processing with GPU. What is difference with this DoParallel (R) and GPU Parallel (Cuda, Python)? Sorry for the many questions.

  3. Note : I could not follow the code properly in Rstudio on cloud thus I followed this code in kaggle notebook. There was some issue with "stopCluster(cl)" and thus running without parallel again was not possible. This was solved using registerDoSEQ().

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