Відео

thank you for making!

thanks

Impressive. Nicely explained providing good information about the steps.

Just clear and simple, easy to understand. Many thanks.

you are fantastic, really thanks from my heart. Have a lovely day

Is it correct to apply scaling(standard scaling in block 7, line 3) after label encoding on categorical column? for example for female: 1, male: 2

The content is really gold. It's good.

Thanks for the outstanding video ! You are amazing, Rashida!!

I can't think of a better content on this subject

You are a very good teacher...Thank you!

wheres the dataset

Thank you so much for this amazing explanation!

thank u soo much mam concept cleared

where is the dataset?

Were is your html version?

4:50 - Count Vectorizer converts to lowercase by default. If do not want that then use lowercase = False 5:25 - Excluding Stopwords use the stop_words argument when initializing the Count Vectorizer object 6:06 - Default Stopwords list also present 7:00 - Max_df argument 9:15 - Max features parameter in Count Vectorizer

great . . .

Thank you . . .

The optimizer 'adam' is not working for me and shows me the error "unexpected incident". The rest worked very well for me!

Awesome explanation! Thank you so much!

Thank you for your clear explanation! Very helpful :)

How you load the data?

Clearly explained. Thank you so much!

Excellent tutorial

What version of tf are your using during making of your video. Currently I am on 2.17.0 but I receive an error when using .ckpt format. ValueError: "When using `save_weights_only=True` in `ModelCheckpoint`, the filepath provided must end in `.weights.h5` (Keras weights format)". Looks like I an only use .weights.h5 or .keras.

I have one doubt like we provide the x_train and y_train to the model for training purpose, and we can test the data by x_,test so I m not getting the purpose of y_test

Thankyou very very much for clearing that concept. I m roaming for one month for this topic but not getting the concept clearly, by watching your video I am on 98% must say

can you provide insurance.csv?

any link for the code ? thanks

very good

Thank you so much for your simplistic explanations!

Nice❤

Nice class thanks

Good tutorial!

Madam I practiced self driving car code by Yolo and CNN can you make a video regarding coding

its really helpfull thanks alot

dfs.loc[idx['school1':'school3', 2019:2020], idx['7th grade':'8th grade', 'Math':'English']] I am getting UnsortedIndexError: 'Key length (2) was greater than MultiIndex lexsort depth (1)' and UnsortedIndexError: 'MultiIndex slicing requires the index to be lexsorted: slicing on levels [0, 1], lexsort depth 1' error. Can you please help. I am also getting the same error for dfs.loc[('school1', 2019):('school3', 2020),('7th grade', 'Math'):('8th grade','Math')]

Nice class👌

Madam can you please suggest me a laptop for aiml

🙏👍🇵🇰

Slowing down, zooming out and picking up new skills if they resonate with us. Thank you so much for the the great content!

Thanks.

why did we convert it the training data to 2d?

Madam suggest any website link for machine learning job's in India

Excellent Explanation and with great concept...Thank you very much👍

thank you very much this helped me a lot hopefully, I will get a good grade !! :)))

Great video. Please can you share the insurance data? It's not visible in the description. Thank you

Why did we use poly.fit, when we already used poly.fit_transform 08:37

could u plz provide the Dataset being used in the video

why did u choose degree 6?