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15:13 MLP Lecture 06 - Clip 05 - Pretraining MLP Lecture 06 - Clip 05 - Pretraining	MLP Lecture 06 - Clip 05 - Pretraining Machine Learning Practical (MLP) Lecture 06, Clip 05 / 05. machine learning deep learning network training images representations learning weights task layer target output input image categories species kind thing labels parts inputs networks From Pavlos Andreadis on October 24th, 2020 2 likes 186 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
37:36 IDS - Week 05 - 02 - Tips for effective data… IDS - Week 05 - 02 - Tips for effective data visualisation	IDS - Week 05 - 02 - Tips for effective data visualisation Designing effective data visualisations and principles for effective visualizations data science rstats plot colors visualization region opinion axis function color levels labels variable things question audience scale regions survey bit bars rest From Mine Cetinkaya-Rundel on October 19th, 2020 0 likes 28 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
06:03 CL - Lecture 4.k - Logic and Algebra CL - Lecture 4.k - Logic and Algebra	CL - Lecture 4.k - Logic and Algebra Last CL video for week 4. inf1a introduction to computation informatics 1 computation and logic logic things predicates properties operations values algebra individuals b. property collection picture variables individual labels combination difference principle functions stuff union From Claudia-Elena Chirita on October 15th, 2020 0 likes 291 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
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 on October 14th, 2020 0 likes 12 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 on June 8th, 2020 0 likes 70 plays 0 Course Code GLHE11086 Licence Type Creative Commons - Attribution
25:46 R Conversations: Demystifying ggplot R Conversations: Demystifying ggplot	R Conversations: Demystifying ggplot In this video I go over a basic introduction to ggplot2 for the R programming language. Some useful resources include: The R Cookbook: http://www.cookbook-r.com/Graphs/ The ggplot2 cheatsheet:… r stats oer ggplot2 plot drive legend wheel highway things theme chart gg gallon miles axis displacement mpg bit color cars dataset control labels From Jill MacKay on October 30th, 2019 0 likes 26 plays 0 Publisher R(D)SVS Licence Type Creative Commons - Attribution Language English Date Created October 30th, 2019
01:52 Classification with PCA features Classification with PCA features	Classification with PCA features Classification with PCA features iaml pca dimension points class variance classes classifier swamps slide space colors point projection alright distribution dimensions coordinates decomposition labels redundancy From Nigel Goddard on September 25th, 2016 1 likes 1,613 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 on September 25th, 2016 1 likes 1,631 plays 0 Licence Type Creative Commons - Attribution
03:46 Overview of k-means clustering Overview of k-means clustering	Overview of k-means clustering Overview of k-means clustering iaml k-means cluster lots question clusters attributes classes examples instance centroid individuals subpopulation means males machine vector labels bitmaps weight algorithm lecture From Nigel Goddard on September 25th, 2016 1 likes 1,900 plays 0 Licence Type Creative Commons - Attribution
01:09 Nearest-neighbor regression algorithm Nearest-neighbor regression algorithm	Nearest-neighbor regression algorithm Nearest-neighbor regression algorithm iaml nearest neighbours labels algorithm point testing numbers training regression classification x. prediction neighbors arithmetic k. class instinct vote instances points distances computes From Nigel Goddard on September 21st, 2016 1 likes 1,672 plays 0 Licence Type Creative Commons - Attribution
01:54 Nearest-neighbor classification algorithm Nearest-neighbor classification algorithm	Nearest-neighbor classification algorithm Nearest-neighbor classification algorithm iaml nearest neighbours training algorithm phase point label examples testing labels neighbors x. class points distances votes vote classes mold exec instances i. From Nigel Goddard on September 21st, 2016 1 likes 1,698 plays 0 Licence Type Creative Commons - Attribution
01:58 Evaluating Classification and Regression Evaluating Classification and Regression	Evaluating Classification and Regression Evaluating Classification and Regression iaml evaluation accuracy labels classification classifier times regression error task measures learning difference alright prediction amount class lecture rome tasks kinds From Nigel Goddard on September 21st, 2016 0 likes 2,166 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 2,790 plays 0 Licence Type Creative Commons - Attribution
05:49 Naive Bayes for Spam Detection Naive Bayes for Spam Detection	Naive Bayes for Spam Detection Naive Bayes for Spam Detection probability predict attribute labels number computer happen occur caption complete review presentation email independence iaml separate naive user thought chance contradictory effects classify password word password times thought thing advertising representation classifier spam word class words bayes emails minus things probabilities nonspam lots classifiers training numbers From Nigel Goddard on September 17th, 2016 2 likes 2,541 plays 1 Licence Type Creative Commons - Attribution
05:16 Supervised vs Unsupervised Learning Supervised vs Unsupervised Learning	Supervised vs Unsupervised Learning Supervised vs Unsupervised Learning iaml data algorithm learning method spam evaluation algorithms output emails training thing tomorrow lots methods task quantity instances structure cases accuracy labels From Nigel Goddard on September 17th, 2016 1 likes 1,926 plays 0 Licence Type Creative Commons - Attribution
03:25 How to Represent Images How to Represent Images	How to Represent Images How to Represent Images iaml data representations attributes image instances guideline predator things similarity images idea pixels bitmap values attribute numbers class representation process pairs labels From Nigel Goddard on September 17th, 2016 1 likes 2,041 plays 0 Licence Type Creative Commons - Attribution

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