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47:46 ASR Lecture 9 part I ASR Lecture 9 part I	ASR Lecture 9 part I ASR Lecture 9: WFSTs for ASR (partial lecture due to technical issues) speech recognition transducer probability bit output symbol weights probabilities point composition word path log input sequence weight pizza outputs grandma recognition loop From Peter Bell on February 15th, 2021 0 likes 15 plays 0 Licence Type Creative Commons - Attribution Non Commercial Date Created February 8th, 2021
10:41 AVLSI Demo 7 - Adding Specs and Debugging Corners AVLSI Demo 7 - Adding Specs and Debugging Corners	AVLSI Demo 7 - Adding Specs and Debugging Corners How to add specs in Virtuoso Explorer/Assembler (same process in ADEXL), run over corners and debug the corners that fail to meet spec. avlsib cadence virtuoso analogue circuits corners millivolts corner process specifications specification couple outputs margin maestro width vgs edge vd vds table transistors saturation device slope From Filip Taneski on February 11th, 2021 0 likes 1 plays 0 Course Code ELEE11073 Publisher Filip Taneski Licence Type Creative Commons - Attribution Language English Date Created February 11th, 2021
52:44 Agnieszka Borowska (Glasgow): Gaussian process… Agnieszka Borowska (Glasgow): Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis	Agnieszka Borowska (Glasgow): Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis Agnieszka Borowska (Glasgow): Gaussian process enhanced semi-automatic approximate Bayesian computation: parameter inference in a stochastic differential equation system for chemotaxis Chemotaxis is… statistics research parameters cell parameter abc regression features estimates model outputs points element point membrane process simulator step cases nodes instance distribution From OLLIE Quinn on February 4th, 2021 0 likes 6 plays 0 Licence Type All rights reserved Language English Date Created January 29th, 2021
07:29 AVLSI Demo 4 - Calculator Basics and Creating… AVLSI Demo 4 - Calculator Basics and Creating DCOP Expression	AVLSI Demo 4 - Calculator Basics and Creating DCOP Expression Basics of using the Cadence Virtuoso calculator and adding DCOP expressions to the ADE output avlsib analogue circuits cadence virtuoso device expression stack calculator outputs point characteristics devices margin millivolts vsat ad cursor thing buffer vds parameter step simulation voltage From Filip Taneski on January 28th, 2021 0 likes 2 plays 0 Course Code ELEE11073 Publisher Filip Taneski Licence Type Creative Commons - Attribution Language English Date Created January 28th, 2021
02:56 Distillation Lecture 1 2020 part 3 Distillation Lecture 1 2020 part 3	Distillation Lecture 1 2020 part 3 Distillation Lecture 1 2020 part 3 column purity bottom specifications trays disposal tools question analysis input energy specification sense streams output outputs concentration ideal inefficiencies From John Christy on December 24th, 2020 0 likes 33 plays 0 Course Code CHEE11023 Publisher John Christy Licence Type All rights reserved The University of Edinburgh Language British English Date Created December 24th, 2020
11:13 ML7: Logistic Classification ML7: Logistic Classification	ML7: Logistic Classification Here, we introduce a logistic classifier and cover how it differs from a linear classifier. Then, we show how its parameters can be learnt by minimising the cross-entropy loss. Finally, we visualise… classifier loss class function probability points point parameters label outputs i. training linear boundary decision side contribution times minus thing From Elliot Crowley on November 6th, 2020 0 likes 6 plays 0
02:39 MLP Lecture 07 - Clip 08 - Learning Image Kernels MLP Lecture 07 - Clip 08 - Learning Image Kernels	MLP Lecture 07 - Clip 08 - Learning Image Kernels Machine Learning Practical (MLP) Lecture 07, Clip 08 / 09. machine learning deep learning image kernels cat pixels kernel feature transformation hierarchy weight grayscale detection edge values contrast outputs input layer net training examples From Pavlos Andreadis on November 2nd, 2020 1 likes 169 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
08:51 MLP Lecture 06 - Clip 02 - Weight Initialization MLP Lecture 06 - Clip 02 - Weight Initialization	MLP Lecture 06 - Clip 02 - Weight Initialization Machine Learning Practical (MLP) Lecture 06, Clip 02 / 05. machine learning deep learning variance distribution weights units output input backpropagation inputs range practice network hour idea outputs beginning problem deviation initialization root expectation From Pavlos Andreadis on October 24th, 2020 1 likes 189 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
20:21 2b - Six Sigma and DMAIC 2b - Six Sigma and DMAIC	2b - Six Sigma and DMAIC Lecture 2b - Six Sigma and DMAIC by Prof Ian Underwood engineering design and manufacture problem plan failures failure customer process analysis root team rule tools implant solution control improvement lot end outputs scope experiments From Lesley Gibson on September 3rd, 2020 0 likes 79 plays 0 Licence Type Creative Commons - Attribution
01:27 Generalization in Machine Learning Generalization in Machine Learning	Generalization in Machine Learning Generalization in Machine Learning point predict labels number instances targets interesting decision system regression build algorithms evaluation accuracy iaml training data tomorrow outputs reason train effects percent accuracy predictor matter future values attributes classifier training classifiers neighbor trees level app model From Nigel Goddard on September 20th, 2016 0 likes 2,952 plays 0 Licence Type Creative Commons - Attribution
01:19 Least Squares Classification Least Squares Classification	Least Squares Classification Least Squares Classification burst predict produced magenta regression aggression caption complete serum regression analysis points iaml spell linear loose drives reason produce complicated effects sound great outlaw linear regression optimization logistic regression action output problem logistic procedure outputs outliers effect decision squares shows green ascent gradient bit From Nigel Goddard on September 8th, 2016 0 likes 3,064 plays 0 Licence Type Creative Commons - Attribution

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