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16:37 RMS2 (20-21): 5.3 RMS2 (20-21): 5.3	RMS2 (20-21): 5.3 model bic aic models values term correction participants sums parsimony difference context bit squares cases log improvement linear predictors variables From Thomas Booth on October 18th, 2020 0 likes 100 plays 0
46:14 IMA, LMS Joint Meeting: Topological methods in… IMA, LMS Joint Meeting: Topological methods in Data Science (1-2 October 2020)	IMA, LMS Joint Meeting: Topological methods in Data Science (1-2 October 2020) An automated programme is used to generate the subtitles on this talk. You can remove the subtitles by pressing CC on the bottom toolbar. Ulrike Tilmann (Oxford) - Homology of random geometric… points manifold boundary point homology radius log function graph question dimension epsilon complex volume sense complexes distance n. union triangle From Liam Holligan on October 9th, 2020 0 likes 6 plays 0 Publisher Liam Holligan Licence Type All rights reserved Language English Date Created October 2nd, 2020
07:44 RMS2 (20-21) 4.2 RMS2 (20-21) 4.2	RMS2 (20-21) 4.2 Research Methods & Statistics 2 (20-21) Week 4 Lecture 2 values variable transformation log function assumptions variables heteroscedasticity outcome residuals normality homoscedasticity errors regression assumption end skewness nonlinearity relations experience From Josiah King on September 18th, 2020 0 likes 202 plays 0 Licence Type All rights reserved The University of Edinburgh
08:08 dapR2 (20-21): 4.4 dapR2 (20-21): 4.4	dapR2 (20-21): 4.4 values variable transformation log function assumptions variables heteroscedasticity outcome residuals normality homoscedasticity errors regression assumption end skewness nonlinearity relations experience From Aja Murray on September 12th, 2020 0 likes 128 plays 0
12:25 Topic 21: Probability Transformation Rule and… Topic 21: Probability Transformation Rule and Its Applications (PETARS, Chapter 4)	Topic 21: Probability Transformation Rule and Its Applications (PETARS, Chapter 4) This video introduces the probability transformation rule, for finding the probability density function of the mapping of another random variable. A derivation of the transformation rule is… pgee11164 output probability input pdf interval intervals x. function density gradient distribution transformation minus y. variable expression delta infinity log roots From James Hopgood on September 5th, 2020 0 likes 72 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created September 5th, 2020
14:25 4.4-part5: Exponential and gamma distribution… 4.4-part5: Exponential and gamma distribution (exercises)	4.4-part5: Exponential and gamma distribution (exercises) . ... minus lambda distribution probability cdf arrivals distance parameter expectation exercise percentile meters x. power mu variable exercises log median deviations From Vesselin Velichkov on July 20th, 2020 0 likes 3 plays 0 Licence Type All rights reserved The University of Edinburgh
02:51 Process Mining Process Mining	Process Mining Process Mining hds process event mining processes care approach models characteristics instance log quality systems discovery techniques model interest domain patients stratification level From Dimitrios Doudesis on June 30th, 2020 0 likes 55 plays 0 Course Code GLHE11086 Licence Type Creative Commons - Attribution
03:15 A Probilistic View A Probilistic View	A Probilistic View A probabilistic formulation of the linear model square probability regression analysis gaussian probabilistically general predicts regression caption complete annoyance probabilistic systems theory 2017 mosquito function iaml noise linear model theory of probability distributions equivalent statistical terminology component effects output estimate likelihood probability theory structure remember solution linear regression algorithms residuals variance problem linear model error log input inverse pseudo method optimization score task From Nigel Goddard on October 1st, 2017 0 likes 2,441 plays 0 Licence Type Creative Commons - Attribution
05:52 K-d tree algorithm K-d tree algorithm	K-d tree algorithm K-d tree algorithm iaml nearest neighbours points tree median branch point neighbors half attribute side instances dataset middle x1 testing leaf base log space procedure subset From Nigel Goddard on September 21st, 2016 1 likes 1,509 plays 0 Licence Type Creative Commons - Attribution
05:16 Decision Tree Entropy Decision Tree Entropy	Decision Tree Entropy Decision Tree Entropy subset logarithms interpretation people measurement number entropy purity determine measure totally pure tells caption complete positive proportion negative pretty percentage iaml random element whatsoever statistical terminology completely basically definition decision trees items uncertainty minus pure set effects bits log bit positives numbers element proportions negatives subsets values end base thing From Nigel Goddard on September 21st, 2016 0 likes 2,724 plays 1 Licence Type Creative Commons - Attribution
03:05 Error functions Error functions	Error functions Error functions iaml optimisation surface weights error training weight model thing minimization likelihood log learning minimum curve dimensions space parameters sort maximization problem regression From Nigel Goddard on September 18th, 2016 1 likes 1,854 plays 0 Licence Type Creative Commons - Attribution
02:35 Optimisation in Machine Learning Optimisation in Machine Learning	Optimisation in Machine Learning Optimisation in Machine Learning iaml optimisation optimization likelihood log lot problem regression model linear mathematics learning machine function property logs sum observations probabilities probability logger whites From Nigel Goddard on September 18th, 2016 1 likes 1,941 plays 0 Licence Type Creative Commons - Attribution
07:48 Regularisation: Concept and Effect Regularisation: Concept and Effect	Regularisation: Concept and Effect Regularisation: Concept and Effect iaml regularisation model lambda solution training error parameter regularization thing polynomial kind points term whites times parameters complexity idea testing era log From Nigel Goddard on September 16th, 2016 0 likes 1,602 plays 0 Licence Type Creative Commons - Attribution
09:04 Learning the Parameters Learning the Parameters	Learning the Parameters Learning the Parameters classification point regression analysis philosophical terminology product individual respect caption complete differential calculus probability gradient computing question experiment iaml log likelihood power statistical terminology independent understand effects likelihood structure individualism data point numerical method transmission differential solution linear regression political philosophy optimization logistic regression analytical output log term input points regression method sigmoid things weights probabilities parameters model place answer From Nigel Goddard on September 8th, 2016 0 likes 2,516 plays 0 Licence Type Creative Commons - Attribution
05:37 Estimating the Bernoulli Distribution Estimating the Bernoulli Distribution	Estimating the Bernoulli Distribution Estimating the Bernoulli Distribution iaml maths probability model likelihood power coin zeros log maximum minus points theta hypotheses times dataset differential numbers probabilities die toss models From Nigel Goddard on September 8th, 2016 1 likes 1,331 plays 0 Licence Type Creative Commons - Attribution
02:14 Estimating Gaussians Estimating Gaussians	Estimating Gaussians Estimating Gaussians iaml maths sigma points formulation matrix likelihood estimate sum log mu gaussian sort density dimensions covariance kind n. component times maine concept From Nigel Goddard on September 8th, 2016 1 likes 1,180 plays 0 Licence Type Creative Commons - Attribution

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