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10:09 lecture 3 part 3 Kaltura Capture recording -… lecture 3 part 3 Kaltura Capture recording - January 24th 2021, 10:27:00 am	lecture 3 part 3 Kaltura Capture recording - January 24th 2021, 10:27:00 am Lecture 3 part 3 naess environment lecture 3 part 3 contents gestalt rows qualities nature sense structures reality gestalts rules painting experience sonata character gusto title soul experiences parts ontology From Pauline Phemister on January 24th, 2021 0 likes 15 plays 0 Course Code PHIL10064 Licence Type Creative Commons - Attribution Date Created January 24th, 2021
28:38 Outer space for right-angled Artin groups - Ruth… Outer space for right-angled Artin groups - Ruth Charney	Outer space for right-angled Artin groups - Ruth Charney Geometry and Topology online seminar series Outer space for right-angled Artin groups Ruth Charney (Brandeis) 10 December 2020 mathematics geometry topology space gamma torus metric action end marking groups generators alright graph picture tourist automorphism tourists edge rows point element angle From GILLIAN KERR on December 10th, 2020 0 likes 18 plays 0 Licence Type All rights reserved Language english Date Created December 10th, 2020
30:45 IDS - Week 10 - 03 - AE - The Office, Part 1 IDS - Week 10 - 03 - AE - The Office, Part 1	IDS - Week 10 - 03 - AE - The Office, Part 1 Predicting IMDB ratings of The Office episodes. Part 1 of 2: Data preparation and feature engineering. data science rstats episode halloween lines episodes things valentine michael season dataframe variable christmas column times thing rows variables jim dataset bit text From Mine Cetinkaya-Rundel on November 23rd, 2020 0 likes 10 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
01:33 CL - 11c - CNF by KM (I) CL - 11c - CNF by KM (I)	CL - 11c - CNF by KM (I) Description Pending inf1a introduction to computation informatics 1 computation and logic half karnaugh problem kind b. moment maps complement piece hub halves columns rows variables things expression result slide g. negation From Haoran Peng on November 12th, 2020 0 likes 225 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
08:32 ML2: Dimensionality Reduction ML2: Dimensionality Reduction	ML2: Dimensionality Reduction In this second video, we motivate why it is useful to reduce the dimensionality of your data, and describe how this can be done linearly, using a transformation matrix. We describe a setup whereby we… matrix reconstruction squiggle points dimensionality transpose transformation point column dataset reconstructions distance era columns dimensions inverse rows dimension x. distances From Elliot Crowley on November 5th, 2020 0 likes 14 plays 0
02:29 CL - 6e - DNF CL - 6e - DNF	CL - 6e - DNF More on blocks of ones (which correspond to conjunctions of literals).This video shows how to use a Karnaugh map to represent an arbitrary Boolean function of four variables as a disjunctive normal… inf1a introduction to computation informatics 1 computation and logic karnaugh map blocks 's form disjunction block pattern literals things conjunctions r. expression naught aig b. zeros rows g. column piece power From Haoran Peng on October 24th, 2020 0 likes 404 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
04:22 CL - 6d - Karnaugh Maps III CL - 6d - Karnaugh Maps III	CL - 6d - Karnaugh Maps III More on blocks of ones (which correspond to conjunctions of literals). inf1a introduction to computation informatics 1 computation and logic karnaugh map things block thing half torus corner rectangle cylinder picture properties power amber values examples round rows columns means room sides From Haoran Peng on October 24th, 2020 0 likes 394 plays 0 Course Code INFR08025 Licence Type All rights reserved The University of Edinburgh Language English
20:01 IDS - Week 05 - 05 - Recoding data IDS - Week 05 - 05 - Recoding data	IDS - Week 05 - 05 - Recoding data Review of data import, data types, and classes with a case study involving recoding data data science rstats income plot levels column bit dataframe religion frequencies traditions function protests character strings bar rows tradition legend sample variable columns From Mine Cetinkaya-Rundel on October 12th, 2020 0 likes 24 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
54:20 IDS - Week 03 - Code along IDS - Week 03 - Code along	IDS - Week 03 - Code along The data come from [TidyTuesday](https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-09-29/readme.md). TidyTuesday is a weekly social data project for the R community. Read more… data science rstats things schools function tuition thing groupby chunk bit cost style island total names rows college questions reason output observations dataframe From Mine Cetinkaya-Rundel on October 8th, 2020 0 likes 14 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
17:25 IDS - Week 03 - 05 - Working with multiple data… IDS - Week 03 - 05 - Working with multiple data frames	IDS - Week 03 - 05 - Working with multiple data frames We have multiple data frames and we want to bring them together using dplyr join functions data science rstats dataframe dataframes scientists join survey rows column things enrollment dates customer class students works death names birth records profession professions From Mine Cetinkaya-Rundel on October 5th, 2020 0 likes 41 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
32:15 IDS - Week 03 - 04 - Working with a single data… IDS - Week 03 - 04 - Working with a single data frame	IDS - Week 03 - 04 - Working with a single data frame We have a single data frame and we want to slice it, and dice it, and juice it, and process it using dplyr functions data science rstats variables function children variable dataframe market things babies count bookings segment rows booking rate adults room operator columns filter dataset From Mine Cetinkaya-Rundel on October 5th, 2020 0 likes 63 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
06:46 IDS - Week 03 - 02 - Tidy data IDS - Week 03 - 02 - Tidy data	IDS - Week 03 - 02 - Tidy data What makes data tidy and why do we care? data science rstats table column columns level dataset rows gender statistics analysis height wars star dataframe summary census countries variables cells row side From Mine Cetinkaya-Rundel on October 5th, 2020 0 likes 48 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
21:39 IDS - Week 02 - 03 - Visualising data with ggplot2 IDS - Week 02 - 03 - Visualising data with ggplot2	IDS - Week 02 - 03 - Visualising data with ggplot2 Syntax and specifics of visualising data with ggplot2 data science rstats statistics species color penguins plot points length bill facet axis function columns grid plots variable depth size visualization legend rows island From Mine Cetinkaya-Rundel on September 28th, 2020 0 likes 44 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
23:51 IDS - Week 02 - 02 - Data and visualisation IDS - Week 02 - 02 - Data and visualisation	IDS - Week 02 - 02 - Data and visualisation Introduction to visualising data in R data science rstats statistics plot function dataset visualization package columns character bit height wars star rows things sets gg observations column survey visualizations From Mine Cetinkaya-Rundel on September 28th, 2020 0 likes 93 plays 0 Course Code MATH08077 Licence Type Creative Commons - Attribution Non Commercial Share A Like
11:23 Why do we need Numpy and Pandas? Why do we need Numpy and Pandas?	Why do we need Numpy and Pandas? Short explanation about the role of numpy and pandas in scientific computing python numpy pandas column numbers columns things lists mathematics plot values lots arrays frame elevation function types dataframe pd rows txt power From Mark Naylor on April 28th, 2020 0 likes 23 plays 0 Course Code EASC09054, EASC08025 Licence Type Creative Commons - Attribution Non Commercial
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 vector phi training input rows error thing times columns plane row linear features From Nigel Goddard on October 1st, 2017 1 likes 3,239 plays 0 Licence Type Creative Commons - Attribution

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