Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners Part - 2 | Simplilearn

This Machine Learning tutorial part-2 video will help you understand what is clustering, K-Means clustering, flowchart to understand K-Means clustering along with demo showing clustering of cars into brands, what is logistic regression, logistic regression curve, sigmoid function and a demo on how to classify a tumour as malignant or benign based on its features. Now, let us get started and understand K-Means clustering & logistic regression in detail.

Below topics are explained in this Machine Learning tutorial part-2 :

00:00 - 01:45 What is clustering
01:45 - 03:59 K-Means clustering
03:59 - 09:06 Flowchart to understand K-Means clustering
09:06 - 31:21 Demo - Clustering of cars based on brands
31:21 - 32:37 What is logistic regression?
32:37 - 34:05 Logistic regression curve & Sigmoid function
34:05 - 57:13 Demo - Classify a tumour as malignant or benign based on features

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What is Machine Learning?
Machine learning is a sub-area of artificial intelligence that enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to new data, these computer programs learn, grow, change, and develop by themselves. There are different types of machine learning - supervised, unsupervised and reinforcement learning.

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[azdfasdfa]

At 24:12, it doesn't want to work with the for loop starting at 0. You get a divide by zero, which leads to an overflow error when it converts the float to an int. It works fine with "for i in range(1, 11)" and "plt.plot(range(1, 11), wcss)."

[SimplilearnOfficial]

We hope this video was useful. The link for the dataset used in the video is provided in the description. Thanks!

[nikhilpetro]

Please note the correction: at 23.56 at line 7 for i in range(0, 11):
24.03 line 7 for i in range(1, 11):
Second argument I.e. range(1, 11) is correctly working.

Thanks a ton for sharing knowledge.Your all learnjng videos are very useful and content is easy to understand. Thank you again.:)

[sitaramsahoo]

Amazing ! Never ever understood K-means clustering with such clarity! Good job team. You are on right track!

[Bena_Gold]

always as expected ..."perfect" ... keep it up ... two thumbs up ...

[jefflee]

It was good. can you do a video all about coding with machine learning?

[davidchipundo]

We need this good accent tutorials. I am from africa the southern part its becomeming harder by day to find tech tuts that we can get the accent . so much appreciation

[SubhankarChoudhury]

How do we predict it on new data? Like if we want to check if the model classifies it as malignant or benign with different parameters.

[shubhamaggarwal]

Can you please tell how we calculated mean vector (centroid).?

[revanthrev]

Is there a next part after this video? I am new to machine learning..I finished part 1 and 2 of your tutorial..so tell me which videos to watch from here on?

[AkashVerma-mgys]

Can I get the dataset? or It is better to pin link of the dataset here.

[machwave]

DataSet :- Can you post a link of datasets in your video descriptions for future videos?

[jobinscaria]

Great learning video, good work by your team. Could you please provide me the datasets in part 1 and 2

[savvys]

Thanks for the tutorials. Trust all is well at your end.

[abdulmanan]

very good sir.also make more videos on other algorithms for machine learning

[prashastinama]

'DataFrame' object has no attribute 'convert_objects'
im getting this error

[sagarsharma]

Thank you for the tutorial. Can you please provide me the dataset for both the examples.

[girishlc]

Anyway's we have the brand name in data, what are we achieving ?
can't we cluster based on the brand name ?
looks like poor question, but can you please explain me ?

[supervince]

Awesome tutorial. Any chance you can share the excel files as well?

[bakarekareem]

I'm still waiting for the dataset, thanks