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Machine learning|Candidate Elimination problem|BCS602 important questions|ML Problems|VTU|eduyodha

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Follow the ENGINEERING IN KARNATAKA ✪ channel on WhatsApp: https://whatsapp.com/channel/0029Vb27q0JKwqSbZewkPh1r 🚀 VTU Machine Learning Module 2 Explained in Simple & Easy Way! In this video of VTU Machine Learning Module 2, we cover important concepts like Covariance, Correlation, Gaussian Elimination Method, LU Decomposition, PCA, LDA, SVD, Find-S Algorithm, Candidate Elimination Algorithm, General-to-Specific Ordering, and Specific-to-General Ordering with easy explanations and examples. This video is useful for VTU CSE, ISE, AI & ML students preparing for exams, internals, viva, and placements. 📚 Perfect for: VTU Machine Learning Notes VTU ML Module 2 Machine Learning for Beginners Engineering Exam Preparation AI & ML Students 🔍 Searchable Keywords: VTU machine learning module 2 Machine learning module 2 VTU Covariance and correlation in machine learning Gaussian elimination method explained LU decomposition in machine learning PCA explained simply Principal Component Analysis VTU LDA machine learning explained Linear Discriminant Analysis tutorial SVD explained in simple words Singular Value Decomposition VTU Find S algorithm in machine learning Candidate elimination algorithm explained General to specific ordering Specific to general ordering Machine learning algorithms VTU VTU AIML notes ML module 2 explained Machine learning easy explanation Engineering machine learning tutorial ML for beginners VTU exam preparation machine learning ML important questions VTU Machine learning Kannada Machine learning English AI and ML concepts explained Supervised learning algorithms Machine learning full syllabus VTU ML module 2 important topics #MachineLearning #VTU #VTUML #MachineLearningVTU #Covariance #Correlation #GaussianElimination #LUDecomposition #PCA #LDA #SVD #FindSAlgorithm #CandidateElimination #ArtificialIntelligence #AIML #EngineeringStudents #VTUNotes #MLModule2 #MachineLearningAlgorithms #PrincipalComponentAnalysis #LinearDiscriminantAnalysis #SingularValueDecomposition #DataScience #AI #MLTutorial #VTUExam #Engineering #CSE #ISE #AIMLStudents #MachineLearningForBeginners #SupervisedLearning #VTUSyllabus #MLNotes #CollegeExams #Education #EDUYODHA

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E
ethan.santos 2 weeks, 1 day ago

Maam naale exm but artha agalilla

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vincent_webb 2 weeks, 1 day ago

I have understood all but I did not understand the step five how to take that final hypothesis

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rolando_zayas 2 weeks, 3 days ago

In g4 the last one will be < ? , ? , ? , G , ? , ? >

I
ianvoid39 2 weeks, 3 days ago

how can you consider positive and negitive based on job offer

matthewmist72
matthewmist72 2 weeks, 3 days ago

Why didn't u consider job offer mam

R
rebecca.jordan 2 weeks, 3 days ago

Mam 5th step artaa aaglillaa🥺

J
julianafliegner841 2 weeks, 4 days ago

And what if we get negative instance again

annshah455
annshah455 2 weeks, 4 days ago

U just wrote specific hypothesis in step 5 what about general hypothesis

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luce.antoine 2 weeks, 4 days ago

Ma'am what u didn't wite general hypothesis in last

J
juancarlos.rolón 2 weeks, 4 days ago

In candidate elimination algorithm if 2 negative attributes are come back to back . what can do

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william_grant 2 weeks, 5 days ago

in 10.54 y did u remove good

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tammy_white 3 weeks, 1 day ago

Pls make 1 shot numericals for all modules...Pls upload for all modules machine learning as we have bcm601 first paper is machine learning on Tuesday...pls pls pls upload all numericals plssss

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gaelhenriquedapaz405 3 weeks, 5 days ago

Follow the ENGINEERING IN KARNATAKA ✪ channel on WhatsApp: /channel/0029Vb27q0JKwqSbZewkPh1r

N
nehaganesh976 3 weeks, 6 days ago

Akka bega cover madi time ella full mod 5 tanka

N
nehaganesh976 3 weeks, 6 days ago

Akka Big Data Analytics(BDA) plzzz😢😢😢