Iris Dataset Analysis (Classification) | Machine Learning | Python

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⭐️ Content Description ⭐️
In this video, I have analyzed the iris dataset in python with various techniques like EDA, Correlation Matrix, etc., The dataset has been trained with different models and got some good accuracy. You can check the testing and deployment of the model in the following video.

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🕒 Timeline
00:00 Introduction to Iris Dataset Analysis
01:24 Import modules and load data using pandas
04:27 Delete unnecessary column in Iris dataset
05:11 Statistics data information
07:01 Preprocessing the Iris dataset
07:57 Exploratory Data Analysis of Iris dataset
16:32 Correlation matrix for iris dataset
20:51 Label Encoding for output class
23:20 Splitting the data for training & testing
25:34 Model Training & Testing for iris species classification
31:45 End

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among the many youtube channels for newbies and new learners, you sir are a legend, very well explained.

abhiavasthi

I've only seen 7 minutes of this video and I already love you!! Thank you very much for taking the time to explain all of this. I will watch all the videos on your list😍

monicapn-fp

honestly this video is the bestttt i have seen many other videos but you sir nailed it !!

Broly_the_broccoli

Thank you very much for the detailed explanation # From Algeria🇩🇿 #😊🙌✨

boualisabrina

The best explanation for beginners. thankyou so much :)

sanchitarajapure

Thnx a lot bro, this video made my day, honestly. Luv u bro 👍🏻👍🏻👍🏻 . Even Udemy mentors don't explain in such details.

ishanpathak

You were getting 100% accuracy because the Jupiter notebook kernel stores the previous model so when you shuffle and re-train your KNN and Logistic model it effectively learns the new patterns and adapts to them. in the end, you end up testing on data it has already seen before.

nicdemai

very nice tutorial... easily thnq much

nikhilpingale

Thanks for your clear tutorial. However, I have a question about correlation. Based on the correlation table, since I am using K-means to cluster, I chose a pair with a correlation value that is neither too high nor too low. Therefore, I selected -0.11, which corresponds to SepalLengthCm and SepalWidthCm. But when I calculated the error using SSE in all cases, the pair with a correlation of 0.96 had the smallest error. Could you help me understand why? Thanks once again!

b-lifestyle

Well explained. Request you to please post series only data /EDA operations in python..

jitendratrivedi

I want to deploy this using flask so how to save model?

HensiThakkar

thank you very much,
my question is which kind of supervised machine learning algorithms are used in this project?

ibrahimahmethan

Thanks a lot for the very well and clear explanation, it is really help

mahaalsalman

Thank you very much, that's super helpful !

souhamahmoudi

This was amazing. Very useful!!! Thank you so much.

cahill

raising this error
ValueError: could not convert string to float: 'Iris-setosa'

Aspirant

The session was awesome.. I have worked on it before... But can you tell me where to start ML and Maths stuff, any channel name?

niteshprajapat

This video was good, but with accuracy how do you conclude what amount of species belongs to diff groups?

kurmarao

Hi I was working in the same way on the google collaboratory. In the correlation part I enterd df.corr(), it says df is not defined. Can you please help me out?

chandanar

Please can i use this same exact process for another dataset for example like a dataset that contains histological images that will be used to detect and classify colorectal cancer

banjofikayo

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