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You are a perfect teacher , you made me understand python well

Wow Great Video! Just what I was looking for. Couldn't quite figure out how to get this to work didn't know I needed a Parameter tied to my calculated field! Thanks

Great tutorial!

nice practical

The bars' horizontal length is same for every bar don't know why. Tried every possible thing to fix it.

Happy with the final output, though was very difficult to follow along

If we have two outputs in multiple linear regression model. What are the steps ?

thanks for this video

Nice video! At 12:21, how can I sort based on category vs quantitative number? I'm trying to create a marketing pipeline to show the $$$ each touchpoint generated along the journey.

Where is the dataset link ?

madam pls do videos on ml using python .

Do you have a guide on how to do multiple variables if they are non linear? Meaning we’d have to use a polynomial method with degrees?

From where to get dataset

I've tried using this code but when I reach the ln[2] the table isn't showing up where could I be going wrong I am using the Jupyter Notebook and honestly am frustrated even after coding for close to 6 hours now 😅

Amazing video! This is my first project ever and I hope to continue further in my career of Data Science!

Could you please upload non-linear regression?

guys, for the last piece of code, what does she put to calculate the difference, ive typed it in until pred_y

Very meaningful session, great explanation 👍

Hello!! I keep getting this popped up message anytime i tried to import the data. Please help! "The cell has not been executed to avoid kernel deadlock as there is another pending input! Submit your pending input and try again"

Thank you for your nice explanation, can you upload more videos other modelling, please? thanks you mam

Great explanation! Simple and easy to follow. Thank you.

Very clear picture of the journey of becoming a Tableau Ambassador. Illustrations are meaningful n self-explanatory. 👍👍

It was difficult to find a video like this. Thank you Megha!

Hello Megha. Great video. But you did apply the scaler function to standardize the days. Why?

This is a very good video! Thank you very much!

Hi Megha, thanks for your video.

It's great that you have the Word document. It would be even better if somehow you managed to share it with the viewers who, I assume, wish to recreate your radar chart.

Really insightful😇

The background music is very annoying. consider reducing the volume next time

Great tutorial!

Hi Megha, is there a way to remove the "Categlory" of the legends in "Categlory; sub-Categlory"? I cannot find any potential way to do it!

Hi Megha, thanks for showing steps by steps. I have a question. Instead plotting the result by "Actual" and "Predicted", can we visualize the predicted vs. actual ''y" for each variable"x"? Can you please advise the codes? Thank you.

Excellent!

Maam pls explain, otherwise how would we understand every step?

Thank you ma'am. This is really helpful 😊

Wow Excellent Explanation 😍😍

Ma'am can we get regression for more than 2 independent variables w.r.t more than two dependent variable??

It got confusing from 6:18 to 8 window.

Thanks for Sharing !

Insightful. Thank you for sharing

Nice video

How to do the path for first part? where to storedata

This is sooooo Great!!!

You explained it beautifully but I'm not gonna use the radial chart in my visualization ever because it's too much work without any added benefit except looking good

how to find the beta coefficients and the constant value

Megha, this is the best tutorial I've found for Radial Bar Charts! You explain everything thoroughly, and I love your incremental approach to creating the calculated fields! This worked perfectly for me! I have shared this technique with all my visualization team members!

After define x & y print statement should be came in " str " how it is possible if all dataset and format as it is copy .🤔

Thx

Hi Megha, thanks for the tutorial. How do you match the sub-category to its category in an excel spreadsheet? thanks

Really great ! Thank you for this tutorial 🙂