Why and When Should we Perform Feature Normalization?

Hello All,
In this Video we will be discussing about when and why should we perform feature scaling

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[simon]

clear, concise and exhaustive. Very useful, i appreciate your work. salutations from Italy!

[VVV-wxui]

Thanks Krish. Such insights are the key and makes the difference. Thanks once again for Sharing with All.

[anubhavsood]

Hi krish,

Could you please make a video on end to end steps to be followed for a ML project. For example...
1. Import dara
2. Impute data
3. Remove outliers
4. Perform univariate EDA
5. Train test split
6. Scale features
7. Call algorithm classes like KNN, random forest, linearregression...
8. Perform k Cross validation to validate which algorithm is suitable
9. Perdorm feature reduction
10.perform feature selection technique

[akshaykrishnan]

Superb sir.. This was the video I was looking for. You cleared all my doubts related to feature scaling in the video

[gvsmchaithanya]

Feature Scaling will be applicable to SVM also I think because in that mostly i taken the data set like the binary classification of the dataset like 0 or 1. In this case of that problem and i have also applied min - max scala by using sklearn library. I think my usage of feature scaling what i applied this may correct.

[siddarthbali]

You mentioned that where ever we use euclidean distance we should apply feature scaling, but what about the computation that involves the cosine similarity, does we should perform normalization in that case and the also the score return by the cosine similarity should be normalized or not???

[AmitYadav-igyt]

How about classification problem problems or In Algorithms like Logistic Regression ? Can we use Feature Scaling?

[syedtasleem]

Sir, please try to solve analytics vidhya amexpert hackthon challenge problem..!!

[pravinacharya]

Do we need to do scaling for time series data and which scaling method would be best

[anandacharya]

Thank you sir for this one more excellent video. I request you to make a video, on how to choose a correct machine learning algorithms . Thank you very much!

[Hurtchie-ez]

so we do scaling either for ensuring correct results (like K mean algorithms or for efficiency like anyone which uses gradient decent - correct?

[junaidlatif]

Sir. I used my data for RF without scaling. Model performance is worst and in - ve value. Because my Y (output) variable range from 10E14-10E20.
I tried many ways. But i found better accuracy when i used standard scaler of Y variable.
Other ways my model performance is worst!
Still my question is: if i used scaler in RF and ensamble method is it right? Can I use it?

[the_imposter_analyst]

This was so helpful!! Thank you so much sir.

[muhammadusmanakram]

can you make a video on how can we make our own dataset and how much rows will be enough for that particular dataset??

[atiladursun]

Hi Karish, do you do Normaluzation before pca or after? Thanks

[ishantyagi]

can i apply standariztion for logstic regression

[divyanshchaudhary]

what to use first Scaling or Transformation ?

[hridayanandadas]

I have trained my model using feature scaling. now i want to predict the real data. do i need to scale whose data also?

[naehalmulazim]

Sir, your lectures are always very helpful. Have a subscriber.
But maybe you might consider writing some of the points on the whiteboard. It became a little hard for me to keep up.

[mahery_ranaivoson]

Do we need to scale values we have when we do prediction?