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url](https://raw.githubusercontent.com/raazesh-sainudiin/scalable-data-science/master/db/week5/10_LinearRegressionIntro/018_LinRegIntro.html) of this databricks notebook and its recorded Uji :\n\n[ 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tool for the basics ideas in linear regression:\n* [http://setosa.io/ev/ordinary-least-squares-regression/](http://setosa.io/ev/ordinary-least-squares-regression/)\n\nThe following video is a very concise and thorough treatment of linear regression for those who have taken the 200-level linear algebra. Others can fully understand it with some effort and revisiting. ","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"9c2d83b5-a540-4556-8556-787c4722ff8e"},{"version":"CommandV1","origId":77568,"guid":"e37c13ce-9733-438e-9fc1-04b9780b6576","subtype":"command","commandType":"auto","position":2.0,"command":"%md\n#### Linear Regression by Ameet Talwalkar in BerkeleyX: CS190.1x Scalable Machine Learning\n**(watch now 11:13)**:\n\n[](https://www.youtube.com/v/0wcMCQ8SyZM?rel=0&autoplay=1&modestbranding=1&start=1)\n\n","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"6e2ab6cb-2966-45f9-9523-85b7aa9abb85"},{"version":"CommandV1","origId":79562,"guid":"33ac03db-2d59-44d7-9985-66586b7b5873","subtype":"command","commandType":"auto","position":2.5,"command":"%md\nRidge regression has a Bayesian interpretation where the weights have a zero-mean Gaussian prior. 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And to write maths in display mode do the following:\n\n$$\\mathbf{A} \\in \\mathbb{R}^{m \\times d} $$\n\nYou will need to write such notes for your final project presentation!","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"70bbee25-7bb3-47b6-adde-0ba56119b129"},{"version":"CommandV1","origId":77570,"guid":"1174c421-267f-4c8d-9936-354252a6c46a","subtype":"command","commandType":"auto","position":4.0,"command":"%md\n#### MillonSongs Ridge Regression by Ameet Talwalkar in BerkeleyX: CS190.1x Scalable Machine Learning\n**(watch later 7:47)**:\n\n[](https://www.youtube.com/v/iS2QxI57OJs?rel=0&autoplay=1&modestbranding=1&start=1)\n\n\nCovers the training, test and validation and grid search... ridger 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