MIS Data Warehouse Overview
13:33
5 жыл бұрын
MIS Big Data
6:47
5 жыл бұрын
MIS Traditional vs Stream Computing
3:30
MIS Database Approach
3:20
5 жыл бұрын
MIS Data Management
2:38
5 жыл бұрын
IS 3 Jug Problem
6:58
5 жыл бұрын
Intelligent System using PEAS
10:09
5 жыл бұрын
MIS 3 Characteristics of Information
3:50
RGB The Color of LIfe
4:05
5 жыл бұрын
MIS 2 Types of Information Systems
7:43
MIS 1 What is Information System
3:29
Concept 29 Map Reduce Structure
2:12
Concept 28 Space Reclamation
1:59
5 жыл бұрын
Concept 27 Safemode
2:03
5 жыл бұрын
Concept 25 Datanode and Heartbeat
2:22
Concept 22 Safemode Start Up
2:29
5 жыл бұрын
Concept 19 Filesystem Namespace
1:52
Concept 18 Data Characteristics
2:17
Concept 17 Namenode and Datanode
1:40
Concept 16 What is Data Block
2:28
5 жыл бұрын
Пікірлер
@burqaavenger04
@burqaavenger04 13 күн бұрын
Shukran!
@flutemelody8503
@flutemelody8503 19 күн бұрын
since its undirected graph,shouldn't we multiply the betwenees centraility result by 2 (for v1,v2 and v2,v1)
@reamabdulsalam524
@reamabdulsalam524 Ай бұрын
Very bad explanation, !!! You didn’t discuss all the probability of the node pairs !!! According to your graph it should be n(n-1)/2 pairs which here it is 15 different edges for example B-C , C-D, A-C , A-B , E-F , ……. You didn’t discuss it so I had a wrong calculation!
@Eesey386
@Eesey386 Ай бұрын
Apne india mein joh bina mba k warehouse management karte unme kya khaamiya rehti
@fractalmadness9253
@fractalmadness9253 Ай бұрын
And the west assembles under one church, as it always should have been.
@jayantszone3076
@jayantszone3076 Ай бұрын
got mistake in taking the minimum value in the second updated matrix, which should be 0.2 instead of choosing the 0.14
@swapnildevkate5380
@swapnildevkate5380 Ай бұрын
p2 p3 will be 0.143 not 0.15
@boyhammer-vj4ph
@boyhammer-vj4ph 2 ай бұрын
7 year later still this video make impacts. from Moscow
@mahakalm395
@mahakalm395 2 ай бұрын
My all doubts are clear now thx you so much. :)
@mkClipsHub
@mkClipsHub 2 ай бұрын
great madam
@avishkasonawane9139
@avishkasonawane9139 3 ай бұрын
thank u plus u explained with diff example
@chiragshrivastava6747
@chiragshrivastava6747 4 ай бұрын
what a great explanation and what a great teacher you are, mam! Thank you for such amazing explanation.
@firstlast-ep5ru
@firstlast-ep5ru 4 ай бұрын
The most amazing explanation of this I've ever seen. Thanks a lot!!
@rakeshgupta4372
@rakeshgupta4372 5 ай бұрын
Wow
@ramsrivastava8291
@ramsrivastava8291 5 ай бұрын
Too bad
@BhavaniKurra-s3t
@BhavaniKurra-s3t 6 ай бұрын
Can u provide how to write code for this one
@Surya_Kiran_K
@Surya_Kiran_K 6 ай бұрын
Thanks so much❤❤ saved a lot of time before the exam
@rajanalexander4949
@rajanalexander4949 6 ай бұрын
Fantastic, thank you
@koyelsarkar675
@koyelsarkar675 6 ай бұрын
This is easy way to understand. Thank you, but one point-for undirected graph we multiplied sum of centrality by 2 (BookSocial media mining by Zafarani & Liu)-Chapter 3.1- Centrality
@wb7779
@wb7779 7 ай бұрын
I watched 3 videos before this one explaining the same concept. They all made no sense to me for some reason. This video made sense right away, wow. I think me and you have something special in common or something! Thanks for the easy to understand explanation, you made my day. 😊
@armaansaini1079
@armaansaini1079 7 ай бұрын
For anyone who thinks its ok to remove the dangling edges, it is not. I removed them in my finals and I got my marks cut.
@SteffiCassandra
@SteffiCassandra 7 ай бұрын
For worst case the definition is wrong
@marwag3941
@marwag3941 8 ай бұрын
thank you ,perfect explain
@mary_chase
@mary_chase 8 ай бұрын
thank you, you just saved my assignment
@B_C77
@B_C77 8 ай бұрын
Thank you very much for the videos. In a directed network, does the network need to be fully connected in order to measure betweenness centrality? Assuming that the network in the example in the video is a directed network and there is no path from a to b, zero divided by zero, doesn't that imply an undefined result? However, some sources state that the network does not need to be fully connected to calculate betweenness centrality and that it can be calculated in a disconnected network or component. What is the correct calculation method?
@Pata-u9r
@Pata-u9r 8 ай бұрын
Great explanation mam, just loved it
@reanwithkimleng
@reanwithkimleng 9 ай бұрын
❤❤❤
@danielgetty7216
@danielgetty7216 9 ай бұрын
I've been trying to figure this out for a couple days for class. Once you showed the MIN(dist) it all clicked. Thank you!
@reamabdulsalam524
@reamabdulsalam524 9 ай бұрын
It ok but it is too complicated I hate statistics
@LastOneStandingg
@LastOneStandingg 9 ай бұрын
Thank You mam, for such easy expalnation
@SUMANTH_JM
@SUMANTH_JM 9 ай бұрын
Video is 6 year ago Aploded 😢 o God please take me to 6 hear ago Value for 6 year time very fast 🥺
@JIUSIZHENG
@JIUSIZHENG 9 ай бұрын
well explained, thank you very much
@iamadi1709
@iamadi1709 10 ай бұрын
Best Explanation
@ThabangSilwane
@ThabangSilwane 10 ай бұрын
is the a way of accessing the slides.This is the best presentation by far
@gowthamreddy825
@gowthamreddy825 10 ай бұрын
nice ma'am have a nice day
@mahmoudabdulhamid4182
@mahmoudabdulhamid4182 10 ай бұрын
how can i have this slides
@rachitbhatt40000
@rachitbhatt40000 10 ай бұрын
So, what is use of HAC? I mean, how to find the optimum clusters amongst all?
@kiirnyok6736
@kiirnyok6736 10 ай бұрын
Thank a lot dear, the explanation was superb!
@soothingszelam2607
@soothingszelam2607 11 ай бұрын
are you taking rounding, for example (0.3+0.29)/2 = 0.59 , so you take rounding to 0.6? Thanks
@tamizhk1610
@tamizhk1610 11 ай бұрын
I want tamil vedio in DGIM Algorithm explanation please
@chaosNinja790
@chaosNinja790 11 ай бұрын
You saved me, I got 37/40 in data mining. Thank you❤
@AnuradhaBhatia
@AnuradhaBhatia 11 ай бұрын
Congratulations ❤️
@andreaaaaaaaa02
@andreaaaaaaaa02 Жыл бұрын
Shit lesson
@lancezhang892
@lancezhang892 Жыл бұрын
Remarkable
@anuroopks7104
@anuroopks7104 Жыл бұрын
Thank you so much.
@Fowrli
@Fowrli Жыл бұрын
I thought PCY and multistage work with hash functions, But here you didnt mention them
@wiseconcepts774
@wiseconcepts774 Жыл бұрын
This is so simplified; I was following Stanford's course on Graph Neural networks and got confused on this, but you cleared my doubt. Thank you so much
@sushantarora5566
@sushantarora5566 Жыл бұрын
very nice explanation maam , please use board and marker , as you have very good method of delivering lectures that will be the best method , and makes it look very simple . but with this also very nice explanation
@ankank4263
@ankank4263 Жыл бұрын
Thanks a lot, so useful information!
@SuzyZou1998
@SuzyZou1998 Жыл бұрын
well explined!!!
@akashonlinehere
@akashonlinehere Жыл бұрын
Short Summary for [Page Rank Algorithm](kzbin.info/www/bejne/rnu4qKamiMaFZ6c) Understanding the PageRank Algorithm for Big Data Analytics [02:10](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=130) PageRank algorithm estimates the importance of a page in Big Data Analytics. [04:20](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=260) Page rank is a measure of the rank of a document based on the rank of documents that are linked to it. [06:30](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=390) Outbound links are important for web page ranking. [08:40](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=520) Calculating page rank using the Page Rank Algorithm [10:50](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=650) Page rank is calculated using a formula based on the number of outbound links. [13:00](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=780) The calculation of page rank involves iterating over the graph and rounding off can lead to inconsistency. [15:10](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=910) Page Rank Algorithm calculates the importance of web pages based on matrix multiplication. [17:14](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=1034) The Page Rank algorithm calculates the page ranking values for different web pages. --------------------------------- Detailed Summary for [Page Rank Algorithm](kzbin.info/www/bejne/rnu4qKamiMaFZ6c) by [Merlin](merlin.foyer.work/) Understanding the PageRank Algorithm for Big Data Analytics [02:10](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=130) PageRank algorithm estimates the importance of a page in Big Data Analytics. - The algorithm calculates PageRank based on votes from other pages on the web. - This calculation is done using a random surfer model and a formula involving inbound and outbound links. [04:20](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=260) Page rank is a measure of the rank of a document based on the rank of documents that are linked to it. - The page rank of a document depends on the page rank of the pages pointing to it. - Page rank is an iterative process that calculates the rank of a page based on the rank of the pages pointing to it. [06:30](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=390) Outbound links are important for web page ranking. - Outbound links contribute to the page rank of a web page. - Dangling links or deadlinks, which have no outbound links, have a negative impact on the page rank. [08:40](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=520) Calculating page rank using the Page Rank Algorithm - The Page Rank Algorithm uses a teleport or damping factor of 0.85 - The initial page rank for all pages is assumed to be 1 [10:50](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=650) Page rank is calculated using a formula based on the number of outbound links. - The page rank of a page is determined by the number of links going out from it. - The page rank of a page is influenced by the page ranks of the pages it is linked to. [13:00](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=780) The calculation of page rank involves iterating over the graph and rounding off can lead to inconsistency. - The calculation should be done without rounding off to ensure consistency in the page rank calculation. - The number of iterations can be increased to achieve a consistent page rank. - Matrix representation is used to calculate page rank. - The teleporter damping factor and Wigan factor are important variables in the page rank algorithm. [15:10](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=910) Page Rank Algorithm calculates the importance of web pages based on matrix multiplication. - Page Rank Algorithm uses matrix multiplication to calculate the page rank. - If the output of the multiplication is consistent, the page rank remains the same. - If the output is not consistent, the algorithm iteratively recalculates the page rank. - The algorithm considers inbound links from other web pages to calculate the page rank. - The number of outbound links from a web page determines the weightage. [17:14](kzbin.info/www/bejne/rnu4qKamiMaFZ6c&t=1034) The Page Rank algorithm calculates the page ranking values for different web pages. - The algorithm takes into account the number of inbound and outbound links for each page. - The page ranking values are iteratively calculated and the damping factor is set to 0.8.