im glad people like you exist. I am simply not smart enough to have figured this out on my own

Absolutely brilliant! Your way of explaining is beyond exceptional. Thank you so much for this simplistic explanation!

Very good tutorial. No nonsense and clean. Thanks

from the bottom of my heart, i want to thank you for your detailed and easy to follow explanation. i dont know who you are or where you are but you have my utter respect. big thanks

I am kinda selfish type of person. Usually I donot like videos nor subscribe channels but how precise and to be the point your video was and I'm utterly impressed as this video was helpfull in clearning my concepts about MLR. Goodluck, Best wishes. You have won a subscriber

I don't know who you are, but THANK you from deep heart for making this content

Very clear instruction, thanks!

Fantastic video.simple to understand

I would've loved for you to squeak in a Residual analysis or whatever is done after you get your R2 values from your test and train group.

Thank you for the tutorial!

Thanks for the amazing insights!

excellent. very helpful. subscribed!

super helpful, appreciate it

Very well explained 🎉🎉 Thanks you so much 🎉🎉🎉

This video is very helpful thank you so much

This video was super helpful

nice video, thanks for your effort ❤

Data isn't my background, but these videos help me understand how to structurally get there. Is there a way to export the predicted charges into a data population for further review. Also, is there a way to adjust the scatter plot dots by a filter on one of the independent variables (i.e. any record where age is 17, make the the plot red color). Thank you!

thanks... this is awesome

Thanks Dear Rashida

how do i go about passing new values from a user?

omg thank you queen❤

thank you for the tutorial

Thank you, god bless

where can i get the dataset that you used

Helpful🔥

how do i plotthe fit line over the data?

i think u can make a function to convert object name into numeric if the the data has many columns instead of writing 1 each 1 like this : for column in df.columns: if not pd.api.types.is_numeric_dtype(df[column]): df[column] = df[column].astype('category') df[column] = df[column].cat.codes df

@regenerativetoday4244

6 ай бұрын

Thank you so much for adding this here. I used this function in some other videos as well.

Can you show us how to do OneHotEncoding?

Nice 👍

Hi, I could find the data but not the code, it's not on your github?

thank youuuuuuuuuuuuuuuuu miss

Great

Very good video. About the model, dont you need to check if R-square need an adjust to trust his income?

@regenerativetoday4244

2 ай бұрын

There are a few different ways to check the model prediction. R-squared error is one of them. It is common for machine learning models to use mean squared error or mean absolute error as well.

How do we access the dataset used?

I have a Different Insight from that i used the Wine data set for that

Can you share the following data please

If I developed a model with an r-squared of 0.2. What do I do to improve the performance of the model?

@regenerativetoday4244

Жыл бұрын

Try different hyperparameters to improve the model and also different models.

❤

please may i ask you why you didn't put (axis = 1) when you drop a column

@regenerativetoday4244

Жыл бұрын

Because it's the default.

Where is the dataset???

Fantastic video. Very simple and to the point. How can I add the regression line to the chart?

@svea3524

11 ай бұрын

do you have the answer?

@shanenicholson94

11 ай бұрын

@@svea3524 let me find it later for you. I got it eventually

@sedativelimit

9 ай бұрын

use plt.plot to draw regression line i.e in the format plt.plot(X_train, reg.predict(np.column_stack((X_train))), color='blue', label='Regression Line')

Erm, I think the method you convert the data "region" is inappropriate. U cant convert the "region" as category since it become ordinal data. I think we should convert each of the region into dummy variables then we can see the coefficient of each region.

@SS-st5uv

3 ай бұрын

Exactly

Please can you send me any link for case study using python polynomial regression (or multi polynomial) with data ? I want to practice.

@regenerativetoday4244

2 ай бұрын

Here it is: kzread.info/dash/bejne/oKWCxqSlcZDQZNo.html

Thank you mam for such a wonderful learning!! I want to know further how can I improve my model accuracy with train score 0.75 and test score -1.12 ??

@regenerativetoday4244

Ай бұрын

First is trying to tune hyperparameters, and also it is normal practice to try different models to find out which model works best for the dataset. Feel free to have a look at this video where you will find a technique for hyperparameter tuning: kzread.info/dash/bejne/naFrk9Wrpbefmqg.html

@chiragahlawat465

Ай бұрын

@@regenerativetoday4244 Thank you so much you have explained it Amazingly and this video made me very happy! Thank you for this video all the rest!!

training and testing on the same dataset?

Good.. but normally we test a model with data that it hasn't seen before, and that's the test split.

Can you please provide the link for the csv file? I'd like to practice the codes on my own as well

@regenerativetoday4244

9 ай бұрын

Here is the link to the dataset: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/insurance.csv Thanks!

@manyasachdeva1511

9 ай бұрын

@@regenerativetoday4244 thank you so much :)

@manyasachdeva1511

9 ай бұрын

Your content is amazing

Could you also upload or provide a google drive link for the data set file. It would be really helpful.

@regenerativetoday4244

7 ай бұрын

Here is the link to the dataset: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/insurance.csv. I am sorry, KZread changed their policy for links.

@santakmohanty612

7 ай бұрын

@@regenerativetoday4244 Thanks a lot !!

x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=0) it works fine but when i swapped the x_train and x_test it gives me error. x_test,x_train,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=0) why this code gives me error. can you please explain me?

@regenerativetoday4244

3 ай бұрын

It should give you error because x_test and y_train have different sizes

@mdrahatislamkhan9966

3 ай бұрын

​@@regenerativetoday4244i dont got your point. sized are same. I wanted to know if i write x_test,x_train .... it gives me error but it i write x_train,x_test.... then it works fine.

What if a dataset has columns with numerical values but with symbols, how to do the cleaning?

@maishakhatun5635

6 ай бұрын

I mean comma or currency symbol, thank you

@maishakhatun5635

6 ай бұрын

have you got any videos that calculate the mean absolute error for evaluation?

hi, I'm not able to find your video on improving the R2 score. Can you show me the video? Thanks

@regenerativetoday4244

3 күн бұрын

You can watch this one that shows how to fine tune hyperparameters that should improve R2 score: kzread.info/dash/bejne/eGVnucSfm9PdnNo.html

Why my coding shows "TypeError: float() argument must be a string or a real number, not 'Timestamp'"? which one could help me to solve this problem, plz!!

@regenerativetoday4244

3 ай бұрын

You need to check the data type of all the columns. If you see any variable is coming as timestamp, that needs to be excluded. Because this tutorial didn't account for datetime datatype. There are different ways of dealing with timestamps. You will find one way of using the timestamp data in this type of models in this tutorial: kzread.info/dash/bejne/fahtwaOCYZXXpLA.html

@jacintaqiu9919

3 ай бұрын

Thank you sooooo much!!!! really helpful:)@@regenerativetoday4244

Its showing a error as "df isn't defined "

what to do when data have null values?

@regenerativetoday4244

10 ай бұрын

I just added a detailed video on how to deal with null values. Here is the link: kzread.info/dash/bejne/dKKarreDm9WzmtY.html

hey I think the formula and the logic is wrong, though implementation is right. Linear regression even though they may seem it is quite different from the just a simple linear equation. The input features what you define as X are in fact vectors. If you compile n with m training example you have a matrix rather than simple linear equation and it turns out to be a matrix multiplication. The addition is something called bias. The W is the weight. Anyway keep up!

@regenerativetoday4244

Жыл бұрын

The bias term in machine leaning term can actually be compared with y_intercept in the linear formula and the weights as coefficients. in y = aX+c, a and X are variables that can be integers, vectors, arrays, or matrices. Same as c. The formula is the concept. I have a detailed tutorial with explanation that shows the linear regression implementation in python from scratch (no libraries), please check if you are interested: regenerativetoday.com/how-to-develop-a-linear-regression-algorithm-from-scratch-in-python/.

On what are you typing your codes this is not vsc?Sorry i am a begginer

@regenerativetoday4244

6 ай бұрын

This is Jupyter Notebook.

@girlthatcooks4079

6 ай бұрын

Thank you so much!

Why did you need to convert to category?

@regenerativetoday4244

9 ай бұрын

Because machine learning models cannot work with strings. It features and labels should be numeric

@Martin-xf8be

9 ай бұрын

@@regenerativetoday4244 Ahh, I see. Thanks for a great video!

Can't download dataset

@regenerativetoday4244

4 ай бұрын

Here is the link: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/insurance.csv

Very clear instruction, thanks!