K Means Clustering in 15 Minutes | K means clustering explained | K means clustering in python

K Means Clustering in 15 Minutes | K means clustering explained | K means clustering in python
#KMeansClustering #KMeansInPython #Unfold Data Science
Hello ,
My name is Aman and I am a Data Scientist.
About this video:
In this video, I explain about K-Means clustering, I also demonstrate how k-means clustering is implemented in python. Below topics are explained in this video.
1. k means clustering algorithm,
2. k means algorithm,
3.k means clustering example,
4 .k means clustering python,
5. k means example in python,
6. what is k-means clustering,
7. how k mean works,
8.k means clustering algorithm python,
9.clustering algorithms,
10.kmeans python,
11.kmeans sklearn tutorial,
12.kmeans example,
13.k means elbow method python,
14.unsupervised learning,
15.k means clustering python,
16.k means clustering,
17.k means clustering algorithm,
18.k means python,
19.clustering in machine learning,
20.clustering python,
21 .k-means in python
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[@karthikraman810]

This is One Video where am searching to know the base line of K-Means Algorithm clearly. Thank you very much for your detailed explanation in simple terms about K-Means algo.

[@UnfoldDataScience]

Thanks for watching Karthik.

[@sandipansarkar9211]

finished watching

[@AnandKrishnanPuravangara]

Thank you Aman! You are the best teacher!

[@balakrishnareddithala8718]

professor from moon.....fly full environment....super sir

[@himanshupathak3090]

Best explanation of K-means clustering... your videos are simple and easy to understand.. waiting for more videos in this series.

[@UnfoldDataScience]

Thanks Himanshu.

[@JainmiahSk]

@@UnfoldDataScience Hi Aman. You are using same data for Training and Testing the Kmeans? and also if we are using two or more clustering algorithms how do you define that which is performing better?

[@soniyajinu6578]

Really nice explanation sir

[@UnfoldDataScience]

Thank you

[@sureshkumar-cn5jr]

Thanks Aman! Great narration, subject is getting clear for beginners

[@snehalhon]

hello sir .... thank you very much . your are best and making data science easy for student like me 10000 likes

[@UnfoldDataScience]

Thanks Snehal

[@megalaramu]

Hi aman, your explanation is easier to understand. Especially elbow plots. Could you please take about performance evaluation metrics in unsupervised algorithms.

[@UnfoldDataScience]

Sure, in next video, I ll pick this topic in detail.

[@ajayreddyvanga6556]

Useful 🙌❤️

[@UnfoldDataScience]

Glad you think so Ajay.

[@btkcodedev]

Amazing Explanation, great

[@UnfoldDataScience]

Thanks For watch Bala.

[@johnfernandes455]

Nice video. Simple n clean

[@UnfoldDataScience]

Thanks for your positive feedback

[@vedprakash8846]

Thank You! this was very helpful

[@UnfoldDataScience]

Thanks for watching Ved.

[@9902152322]

keep exploring sir, explanation is excellent. waiting for the next video. thank you

[@UnfoldDataScience]

Welcome

[@johndaniel7569]

Really a good info on K Means!! Thanks

[@UnfoldDataScience]

Glad it was helpful!

[@dilnawazahmed949]

You r just awesome explained difficult things in an easy way ✅

[@soheilaahmadi4807]

you are great. May God bless you

[@vishnujatav6329]

Really good

[@UnfoldDataScience]

Thanks Vishnu.

[@achumohan5908]

Thank you bro for your detailed explanation 🙂 Kuddos !!👏

[@UnfoldDataScience]

Welcome Mohan.

[@ahmadjaradat3011]

thanks

[@krishnamishra8598]

When u say mean of data points.. will it be mean of difference between randomly initialised centroid & data points?

[@ML_Engineerr]

Very helpful

[@milliesadie486]

Thank you

[@amalageorge394]

excellent

[@mikuniaroz]

Great explanation! love it

[@dees900]

great video. thank u.

[@dr.shambhujha3999]

Rather than choosing random centroid id is better to choose centroid with maximums distance

[@rusiraliyanage6643]

very clear explaination sir :)

[@sainathpawar9655]

Very nice explanation.can you please explain DBSCAN as well. And difference between KMeans and DBSCAN

[@UnfoldDataScience]

I will add dbscan video as well Sainath. Thanks for watching.

[@ganeshgunjal4220]

explanation is very nice and understandable. please provide dataset link also. i am stuck there.

[@UnfoldDataScience]

check description

[@vaishalikadwey4457]

wonderful explanation, very informative video. Sir please make video on PAM CLARA also

[@UnfoldDataScience]

Sure I will

[@sangeethaagoudar2175]

Thank you sir!

[@nandinimatamacedatascince1407]

basically we need to have intra cluster has to be minimum and inter cluster distance has to be maximum in clustering method, how will it taken care by at a time in clustering . could you explain about it ? thanks in advance :)

[@UnfoldDataScience]

To achieve that, points will be shifted between clusters in various iterations of model training as explained. Wherever those two criteria are satisfied, it will be chosen as final allocation

[@shaikhuzma786]

❤

[@datascienceworld7041]

Incase of Inertia it will sum up the distances For example suppose k = 2 it will create 2 clusters and it will add the 2 cluster to show the Inertia value??? Is that correct

[@travelofftradition]

Hi Aman!! I'm currently studying in Germany. Thanks a lot for explaining K means in plain english. This is by far simplest video to understand the concept. However I have one doubt. Suppose we have 5 variables or 10 variables in a table. Then how K means works? In your case there were only two variables so the scatter plot can be easily made. If there are 5 variables then also K means develop the scatter plot first and determine euclidean distance or how does it works? In addition to that I have another doubt, I have data related to bank customers in 5 tables, how would you suggest to apply K means when we have multiple tables? Thanks Mohit

[@kunals.1161]

Hello Sir, Thanks for such a informative video. I have a request, will you please take a session on how we can implement Logistic Regression with Regularization (Ridge or Lasso) and Cross Validation(K-fold) , as I always get stuck there!

[@UnfoldDataScience]

Thanks kunal for asking. I will try to create video on it.

[@santoshr1708]

Thank you sir

[@karthickkarthi2401]

hi sir i think u are fine i have doubt regarding programming language in python i know the basics the requirements that satisfies the ML, DS, DL is that enough i don't know the core python can u pls tell me iis it sufficient

[@UnfoldDataScience]

For starting its ok Kathik, don't count it as road blocker. You can learn many things on the job. Just be mentally prepared to do so.

[@karthickkarthi2401]

@@UnfoldDataScience ok sir tq

[@ratheeshmsuresh7368]

Brother, K Value I have got from the Elbow Method and Silo Score (K Value) seems to be different. What does it tells? Am I wrong

[@alkabuxi8592]

Very well explained. Can i use the concept of k means clusterring in R language.

[@UnfoldDataScience]

Yes ofcourse

[@shreyjain6447]

If I get a real world dataset where I need to perform clustering, should I first split into train, test and valid and then scale and perform clustering algo? Also if I want to evaluate how accurate my clusters are how should I proceed about it?

[@UnfoldDataScience]

Answer of first question - yes. Second question, please watch this video: kzbin.info/www/bejne/lZvKYoh8pMqZZ8U

[@shreyjain6447]

@@UnfoldDataScience Do you have a video on clustering where you split the data into train test and valid? Because every video/tutorial I have seen does not perform splitting on a clustering algorithm. A link to the video/article where this is done would be enough!

[@vanamanu4283]

Brother will you do a video fro adaptive-K means algorithm brother

[@UnfoldDataScience]

Sure

[@GhostRider....]

very nice explanation and implementation sir, please provide the excel file also(file is not present in google drive)

[@UnfoldDataScience]

oops, I searched and could not find , its a simple excel only, please populate some numbers in two columns and you can use as customer data.

[@61_shivangbhardwaj46]

Thnx sir😊

[@UnfoldDataScience]

Most welcome

[@hardikvegad3508]

Amazing Explanation Aman. Would you please show us with code how to get a performance matrix such as silhouette or any other which you consider worth sharing. Thank you.

[@UnfoldDataScience]

Thanks Hardik. Yes good question. All these I will discuss as part of interview questions on K-means which is next video planned.

[@gowthamjeevanantham6144]

hi just one doubt initializing the centroid second step which is randomly initialized or is there specific reason to select

[@suryakanth1000]

In this example, you have used two columns in the dataset for clustering. At the end when visualizing the clusters, the plotting was done between these two columns. But if we have more than 2 columns in our data, how do we visualize the clusters after clustering?

[@rajathslr]

Try to imagine a collection of points levitating in ur room(x,y, z axis) and you use a balloon to cover them all without moving the points. That balloon is the cluster and the points are spread across xy and zy axis.

[@UnfoldDataScience]

Very good answer Rajath.

[@nishah4058]

Didn't gety rajath k..how you decide when you have no of variables more than two

[@archanamaurya89]

How do we determine the number of iterations to move the centroid and what if it still not enough to classify the datapoints into correct clusters.

[@UnfoldDataScience]

We do not know in advance. We need to hit and trial.

[@archanamaurya89]

@@UnfoldDataScience thanks for the reply

[@datafuturelab_ssb4433]

If more than 2 features are there then how to implement kmeans. Which features are considered for clustering.

[@UnfoldDataScience]

Good question, if more features are there all the features will go as a dimension to algorithm. Also there are feature reduction technique such as PCA which is used in this scenario.

[@kunals.1161]

@@UnfoldDataScience Hello Aman Sir, will you please take such a data for example and explain it with python practicle?

[@datafuturelab_ssb4433]

@@UnfoldDataScience thanks for the guidance Related query If we do pca in that scenario how we can make conclusion out of that.

[@UnfoldDataScience]

PCA will make us loose the meaning of original variable. So any analysis on original variables post PCA will be difficult. However, PCA can be useful for better clustering in multi variable scenario.

[@datafuturelab_ssb4433]

@@UnfoldDataScience thank you very much

[@artificial-intelligence5753]

Is there a formula for inertia?

[@UnfoldDataScience]

Inertia formula in this context, I am not very sure, I will get back on it.

[@gadmuhirwa5226]

from request import PandaRequest ModuleNotFoundError: No module named 'request'

[@ajmalbashaa881]

Apply K-Means clustering with K=2,3,4,5,6,7,8,9,10 for all features of 56 datasets and find the optimal number of clusters using the Silhouette Coefficient and Davies-Bouldin index. 2. Store your results with a single excel file with multiple rows, i.e., one row for each project and Column used to represent Silhouette Coefficient and Davies-Bouldin index. 3. Represent your results using visualization techniques. Note:56 datasets include 56 excel sheets with 125 rows and 20 columns. 21st clumn indicats class. kindly, help me with this.

[@UnfoldDataScience]

This looks like your project/assignment. What help do u expect from me?

[@ajmalbashaa881]

@@UnfoldDataScienceyes, Can you please share your mail id? I can show the details to you.

[@jamesa.esquivel4158]

Excellent Tutorial! May I know where can I download the CustomerData.xlsx dataset? Thanks!

[@UnfoldDataScience]

drive.google.com/drive/folders/1XdPbyAc9iWml0fPPNX91Yq3BRwkZAG2M

[@jamesa.esquivel4158]

@@UnfoldDataScience Hello sir! The folder does not include the CustomerData.xlsx file. Where can I download a copy of it? Thanks!

[@ganeshgunjal4220]

@@jamesa.esquivel4158 same here. if u foound, can u paste link here please?

[@battingbaba7077]

Make sure to tell ur concept in normal language it is more complicated

[@UnfoldDataScience]

Ok

[@gadmuhirwa5226]

but they are always giving me this error: ModuleNotFoundError: No module named 'request' after installing requests module the problem remains

[@UnfoldDataScience]

Time to time module gets updated, pls check in latest documentation

[@rajankp5735]

Sir how it applicable to machines??

[@UnfoldDataScience]

Same way like typical ML algorithms

[@akashghuge8235]

Why K means, why not M means or A means?

[@UnfoldDataScience]

We will discuss in interview questions video.

[@pushpapawar4045]

Sir nieve bayes learning please

[@UnfoldDataScience]

Will add :)

[@hermannalidje6442]

Hey guys I am a new student in data science please somebody that can train me I will pay for Thx

[@gadmuhirwa5226]

thank you

[@muhammedthayyib9202]

Consider 2 clusters. What if the distance of a point is equal to both clusters. ?

[@UnfoldDataScience]

Highly unlikely, consider multiple dimension and distance metric calculation, it will go upto many decimal points.

[@muhammedthayyib9202]

Ok. Thank you 💟