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12:16 Fitting Parameters Fitting Parameters	Fitting Parameters How we fit parameters for the linear model multiplying thoroughbred racehorses dot product loss functions caption complete inverse dimensions parameters 1st column matrices column internet search engines training instance 2017 scientific method analytic geometry function iaml product statistical terminology data points transpose practice component dimensional case vectors estimate equations matrix top row abstract algebra input features minimize linear algebra constraint linear regression geometry points model statistical models effects From Nigel Goddard on October 1st, 2017 1 likes 1,890 plays 0 Licence Type Creative Commons - Attribution
01:47 Removing the Scale Removing the Scale	Removing the Scale Removing the Scale arbitrarily hyper defined number potent height minimum hyperplane caption complete scale versus iaml direction multiple degree predicting perpendicular plane effects infinite remember observation constraint geometry freedom remove vector error support vector machines margin From Nigel Goddard on September 8th, 2016 1 likes 1,765 plays 0 Licence Type Creative Commons - Attribution

12:16

Fitting Parameters

How we fit parameters for the linear model

From Nigel Goddard on October 1st, 2017 1 likes 1,890 plays 0

Licence Type

Creative Commons - Attribution

01:47

Removing the Scale

From Nigel Goddard on September 8th, 2016 1 likes 1,765 plays 0

Licence Type

Creative Commons - Attribution

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