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02:11:46 DDC Session 5 Recording DDC Session 5 Recording	DDC Session 5 Recording Recording of session 5 (plotting) of data-driven chemistry 2021-22. data-driven chemistry python plot thing things bit point figure plots carbon axis axes colour sort label values matplotlib formula points column melting angle From James Cumby 0 likes 40 plays 0 Course Code CHEM08031 Licence Type Creative Commons - Attribution Language English Date Created October 21st, 2021 Retain Source File Yes
02:06 Target Detection and Recognition of Ground… Target Detection and Recognition of Ground Penetrating Radar using Morphological Image Analysis and Graph Laplacian Regularisation - Jun Dong	Target Detection and Recognition of Ground Penetrating Radar using Morphological Image Analysis and Graph Laplacian Regularisation - Jun Dong SSPD 2021 Poster Lightning Presentation SessionPresenter: Jun DongPoster Title: Target Detection and Recognition of Ground Penetrating Radar using Morphological Image Analysis and Graph Laplacian… sspd 2021 method image target graph detection regularisation slide alarms result process ossification edge label pre node gar iodine feature processing erosion From Joseph Burchell 0 likes 4 plays 0 Licence Type All rights reserved Language English Date Created October 14th, 2021
03:20 Using variables in Xerte Using variables in Xerte	Using variables in Xerte Using variables in Xerte xerte xerte online toolkit answer question answers field feedback letters submit row grid properties numbers cheque distractors prompt play menu drop lowercase label brackets From Alison Christie 1 likes 15 plays 0 Publisher Alison Christie Licence Type All rights reserved The University of Edinburgh Date Created July 16th, 2021
03:03 Saat Mubarrok EVA Talk Preview Saat Mubarrok EVA Talk Preview	Saat Mubarrok EVA Talk Preview This talk has captions. You can remove these by pressing CC on the video toolbar. Name: Saat Mubarrok Talk Title: Annual Maximum Precipitation in Indonesia linked to Climate Variability: Extreme… eva icms theory solution model analysis extremes climate variability maximum annual values rainfall change indonesia base maxima oscillation station science dog label ocean amnesia place nation iud comparator demand millimetre From Anna Munro 0 likes 13 plays 0 Licence Type All rights reserved Language English
57:00 ASR Lecture 10 (part 2); Lecture 11 ASR Lecture 10 (part 2); Lecture 11	ASR Lecture 10 (part 2); Lecture 11 ASR Lecture 10 (part 2): Neural network models (1); ASR Lecture 11: Neural network models (2) speech recognition network networks probability bit speech recognition features output layer error weights outputs label delta things function hmm term lecture layers From Peter Bell 0 likes 73 plays 0 Licence Type Creative Commons - Attribution Non Commercial Date Created February 22nd, 2021
57:46 MLP Interviews - Leonie Bossemeyer MLP Interviews - Leonie Bossemeyer	MLP Interviews - Leonie Bossemeyer Machine Learning Practical interviews - Winter 2020 - Session 2/4. Leonie Bossmeyer is an MSc graduate in Data Science at the University of Edinburgh, and is currently an MSc student in Quantitative… machine learning deep learning copulas density estimation embeddings gan generative adversarial networks normalising flows images image things distribution kind model thing lot bit buildings week damage question variables idea dataset questions flow task label From Pavlos Andreadis 1 likes 51 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
05:12 CL - 14e - DFA (II) CL - 14e - DFA (II)	CL - 14e - DFA (II) We look at the representation of DFA in Haskell (using lists to represent the sets of the formal definition).In this video the code isDFA is defining what counts as a DFA when we use the black-hole… inf1a introduction to computation informatics 1 computation and logic hole transitions transition start dfa diagram arrow things q1 fsm convention string typing q. function q0 label beginning trace place From Haoran Peng 0 likes 179 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
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 0 likes 12 plays 0
10:51 ML6: Linear Classification ML6: Linear Classification	ML6: Linear Classification In this video, we are introduced to linear classifiers. These have parameters which weight input features, and output a scalar that is used to assign a point to a class. We learn that these… parameters classifier function loss output vector point error linear points respect bias parameter label hair toys times weight gradient minus From Elliot Crowley 0 likes 11 plays 0
17:00 IDS - Week 04 - 06 - AE: Hotels + data types IDS - Week 04 - 06 - AE: Hotels + data types	IDS - Week 04 - 06 - AE: Hotels + data types Application exercise walkthrough: Hotels + data types rstats data science character dollar function axis month label package months factor integer bit labels scales dataframe vector plot variable levels arrival visualization From Mine Cetinkaya-Rundel 0 likes 37 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
30:57 IDS - Week 03 - 07 - AE: Hotels + Data wrangling IDS - Week 03 - 07 - AE: Hotels + Data wrangling	IDS - Week 03 - 07 - AE: Hotels + Data wrangling Working through AE 04: Hotels + Data wrangling data science rstats bookings document adults exercise children adr chunk output function room babies error things variables resort baby arrival result child label From Mine Cetinkaya-Rundel 0 likes 52 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
04:08 Methods for Analysing Clinical Text Methods for Analysing Clinical Text	Methods for Analysing Clinical Text Methods for Analysing Clinical Text hds language processing machine sequence learning model vector techniques methods patient markov treatment medicine precision sense speech sequences labels label text From Dimitrios Doudesis 0 likes 201 plays 0 Course Code GLHE11086 Licence Type Creative Commons - Attribution
01:29 Economic Democracy Block3 v4 Economic Democracy Block3 v4	Economic Democracy Block3 v4 Welcome to Economic Democracy: The Cooperative Alternative, our MOOC about worker-owned and worker-controlled firms. We often hear that political democracy is the best available form of… survey secondly exercise economy general course including carry firstly economic democracy labour-managed provided mooc union workers label start noting capital import firms caption complete worth centrally firm couple exercised labour-managed. effects ownership socialist points firstlt soviet From Nuria Fraile-Diaz 0 likes 6 plays 0 Licence Type All rights reserved The University of Edinburgh Language english
02:47 Neural Networks Neural Networks	Neural Networks Neural Networks iaml units input weights weight output vector class thing features label unit things inputs reason training probability end neurons layer neuron From Nigel Goddard 1 likes 1,588 plays 0 Licence Type Creative Commons - Attribution
09:11 K-means for image representation K-means for image representation	K-means for image representation K-means for image representation iaml k-means patches image patch vector feature labels vectors lots representation cluster grass images color attribute bunch label histogram problem representations occurrences From Nigel Goddard 1 likes 1,989 plays 0 Licence Type Creative Commons - Attribution
03:29 Number of nearest neighbors to use Number of nearest neighbors to use	Number of nearest neighbors to use Number of nearest neighbors to use iaml nearest neighbours validation training class dataset values performance knn label middle classifier boundaries decision classifications algorithm procedure examples moment error setting equals From Nigel Goddard 1 likes 2,190 plays 0 Licence Type Creative Commons - Attribution No Derivatives

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