now that is a really good perspective of how first it looked like outlier but they were in real not , thanks to share this perspective. good video. would love to see more such videos.

thankyou sir I used label encoding method for my project😊 u explained in very easy in simple way

Superb and simplified video presentation...Thank you.

Thanq very much sir

Thanks :)

super sir ,thank you soo much

subscribed, thank you!

Hi. Can you please take me a paid tutorial for a case study of australian vehicle prices from kaggle? Just one session will be enough.

I'm getting true or false instead of 0 and 1 after applying the dummies. Why is that?

Can you please give a piece of code from which we can get the number of categorical columns and numeric columns in the whole dataset

Where can I find this exact code ? And instructions/tutorial how to setup/use for someone who is not a programmer.

Excellent work! I have been working on it for two days, but I did not grasp the main concept. However, after watching the video, I now understand the whole concept. Is my use of 'dose' correct? Also, please check the entire sentence

Sir for data analytics Imp Library

❤ and hug. ❤❤❤❤.

you should continue your videos on ML algorithms you made my day everything you are explaining is in a simple way please do some more videos das

we can also remove outliers using zscore

Hi sir, iam new subcriber. Very good explanation in simple terms. Tq somuch.

sir please come with the best accuracy model of titanic dataset of kaggle

Sir... I didn't know how to download cars files csv can you share the link ple

thank you brother for the value that u have provided thanks alot

I want to contact with you

Hi Sukamal, great explanation. For symboling, can we convert the scale to min-max(0-1) and then apply sqrt?

Im having error even after converting categorical values df value still shows object type

Thankyou❤

Could you please share the link for Descriptive Statistics Video?

i have been working on it for long time , you made it simple .. thank you

Thanks for the information Sukamal. The way you are explaining is way simple and easy to understand for beginners. Keep it up!!!!!!!!!!!!

This looks amazing sir!

sir how to remove outlier on large dataset and also, not like this one or two, it have many outliers per feature

Hello DAS Sir, Could you please help me or provide here a descriptive statistics video link. Not able to find out. Any update

Where can I learn this

😀There was no skewness in the opinion of your watches. They were unanimous in that it was a GREAT video. I definitely agree. Thanks.

I appreciate your efforts, thanks for the playlist. hope you will do more videos covering all possible topics. Keep uploading more videos😊

Time saver ,thank you so much🙏

your video is helpfull.you r saying that highly correlated features with the target.we no need to perform any transformation.will this impact the accuracy of the model.plz reply

what do you think if we create a function and loop over every brand and using traditional outliers detection formula and removing outliers?

how can i handle missing strings valuse without removeing them

Hi can you pls share the video for discriptive statistics ?

#name sns is not defined. what am i doing wrong here?

This is a very good video series. Thank you for sharing. All concepts are now crystal clear. Hope you are creating more content. Channel subscribed!

crystal clear

Sir i want to become a data analyst. Please guide me.

Very informative video. Thanks for sharing.

I've never seen such an easy explanation 🤝

hello sir how to remove the negative skewness

nice explanation sir, keep posted these kind of informative videos

very well explained!

This whole playlist summarizes most of the tasks. Thanks for these tutorials.

Very very useful.

sir can u give me the link of your notebook and what about machine learning