Complete Linkage⛓️ Clustering with Example | Clustering in Unsupervised Learning | ML

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00:00 – Introduction
00:23 – complete linkage
01:02 – example

Complete linkage clustering, also known as the farthest neighbor method, is another type of hierarchical clustering. In this method, clusters are merged based on the maximum distance between points in each cluster, forming clusters that tend to be more compact and spherical compared to single linkage clustering.

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We have end semester exams in 10 days and this man has come to save us!

shreyaslinge
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Superrr se uperrrre😊 sir ji tusi great ho...
Very helpful videos..

shivamprajapati
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I was going through some of your old videos, we can literally see sir transforming over the course of years, But sir you have lost weight it seems, old healthy sir is what we miss. :)
But the efforts and the way of explaining hard concepts in a better understandable way remain constant ❤

rohitshidid
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Mazedaar sir.

Sir kindly upload videos of machine learning program using python.

vishwassharma
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Sir humare december se end semester ka exam hoga. Ek request hai ki aap please jaldi se jaldi ml ke sare topics cover karwa denge to bohot achha hoga... Har exam se pehle apke videos dekh kar hi exam dene jate hain humlog...

abhisheklayek
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Let G be the set of all 2 x 2 matrices ( a b c d ) where a, b, c, d are integers modulo p, p a prime number, such that ad - bc ≠ 0.

momin
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Exam Topic:

Unit 1:-

Supervised Learning (Regression/Classification)

Basic methods: Distance-based methods, Nearest-Neighbours, Decision

Trees, Naive Bayes

Linear models: Linear Regression, Logistic Regression, Generalized

Linear Models

Support Vector Machines, Nonlinearity and Kernel Methods

Beyond Binary Classification: Multi-class/Structured Outputs, Ranking


Unit 2:

Unsupervised Learning

Clustering: K-means/Kernel K-means Dimensionality Reduction: PCA and kernel PCA

Generative Models (mixture models and latent factor models)

Unit 3

Matrix Factorization and Matrix Completion

Evaluating Machine Learning algorithms and Model Selection, Introduction to Statistical Learning Theory, Ensemble Methods (Boosting, Bagging, Random

Forests)
Unit 4
Sparse Modeling and Estimation, Modeling Sequence/Time-Series Data, Deep

Learning and Feature Representation Learning Scalable Machine Learning (Online and Distributed Learning)

Unit 5

A selection from some other advanced topics, e.g., Semi-supervised Learning.

Active Learning, Reinforcement Learning, Inference in Graphical Models,

Introduction to Bayesian Learning and Inference

Unit 6:

Recent trends in various

learning techniques of classification methods

machine learning

and classification methods

abhisheklayek
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Literally tomorrow is my exam and you saved me!!!

BR-
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Sir pls ML ka sara topic jaldi jaldi upload kijiye December se exam h 😢its a humble request

PayelDalal
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Sir if 2 minimum similar values r there then which one to select

lightsacross
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UGC NET computer science and application ke liye konsi book lene h sir

guglothvijaykumar
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Sir please upload all videos of machine learning

Pujakumari-dqvq
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can you please tell me how i can do complete link clustering with similarity matrix?

AR.STUDIO
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Sir please make a video in Hidden Markov Model(HMM).

ankitakumari
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Sir plz dsssb ke liye playlist bna do plz
Ya fir koi best source bta do plz sir

rajeshwaripahal