Data Cleaning/Data Preprocessing Before Building a Model - A Comprehensive Guide

great video !!

good job👌👌❤❤

Thanks a lot for this video!

Brown Kevin Moore Michael Smith Paul

Thanks bro for your informative video. This video saved me from such a mess which I was not able to understand

Thank u for this ,,, can you please tell us in case of date data?

Hi Ankith, thanks for the turorial. I do have a question can we do missing value treatment before EDA ?

Please provide notes also

always an Indian...

Hi, well structured turtorial. Systematicallly for understanding what to do in a first data inspection. Thank you!

Awesome tutorial bro!! Thanks!!

sir.. do i need to fix the skewness before encoding and scaling?

I love your lesson, you explain very clearly. Thank you.

Can I use interpolation instead of mean or median if I have time series data with missing numeric values?

Best

Excellent explanation, now only i understood the preprocessing

I like the layout, very professional and shows exactly each process (what it is) step by step tysm

good brother

Superb video

Overall very a good video. Would've been great if you add specific section for continuous and categorical data types. Another point, I don't understand why you showed the correlation matrix if you didn't use it to filter out highly correlated features (there a couple that were fully correlated and I assume some that were highly correlated).

Thank you so much for this video❤

Thanks for the video, brother, love it

you forgot one step step 8: Normalization. who else notice in the video. Thank you so much for the video.

Thanks for the free lesson💌

I want to add something.. when you are dealing with missing values, lets say for the polio column. You should replace those value for the mean of polio of the corresponding country, if you do the mean overall you might get a slightly different value then let say find the mean of polio in Yemen and replace it by it.. So its always good to think of ways to not generalize much and replace by more specific realistic data

while filling the missing values you also filled the life expectancy you previously said that the Life expectancy shouldn't be touched etc . I think you have performed the work which you said to avoid

nice explanation

upload more projects related to the data scientist

can i do this on kaggle? following the same steps?

I am truly at a loss for words to express the value of this tutorial. It is incredibly insightful, educational, and highly informative. A perfect roadmap for beginners. My sincere appreciation to the presenter for such a fantastic session!

So much details & good explanation sir .. Thank you so much for the video

This is the best tutorial I have come across as a machine learning student. This has given me the entry I needed to get shit done.. Thanks a lot Ankith

@Ankith Kindly Share the notebook as well please.

sir why you Missed Normalization ? (step 8)??

If the missing values are less than 1% should we drop the columns?

❤ thank you 😢😊

Where can i get the notebook ?

AMAZING Video, such a great job ankith! within 12mins of video i knew that this was too too amazing the clarity of explanation. Thankss ton @learn with ankith

nice

ot yul

Nice tutorial!

Where can I find codes?

how you will find the continuous and discrete value did we have any code for that

my favorite tutorial

This was very informative for a beginner. awesome