im glad people like you exist. I am simply not smart enough to have figured this out on my own
@anis.ldx1
7 ай бұрын
Absolutely brilliant! Your way of explaining is beyond exceptional. Thank you so much for this simplistic explanation!
@souravdey1227
2 жыл бұрын
Very good tutorial. No nonsense and clean. Thanks
@maheswaraardhani323
6 ай бұрын
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
@inamhameed4963
2 ай бұрын
Great video. Please can you share the insurance data? It's not visible in the description. Thank you
@christophermiller4637
4 ай бұрын
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!
@nevermind9708
9 ай бұрын
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
9 ай бұрын
Thank you so much for adding this here. I used this function in some other videos as well.
@analyticalmindset
Жыл бұрын
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.
@muhammadaalimisaal8453
Жыл бұрын
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
@albertjohnson8605
Жыл бұрын
I don't know who you are, but THANK you from deep heart for making this content
@RaihanRisad
6 ай бұрын
where can i get the dataset that you used
@mdrahatislamkhan9966
6 ай бұрын
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
6 ай бұрын
It should give you error because x_test and y_train have different sizes
@mdrahatislamkhan9966
6 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.
@raymondkang1329
Жыл бұрын
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
5 ай бұрын
Exactly
@ShouqAldosari
2 ай бұрын
thank you very much this helped me a lot hopefully, I will get a good grade !! :)))
@zishankhan2763
8 ай бұрын
Very clear instruction, thanks!
@Habbodonald
4 ай бұрын
Very good video. About the model, dont you need to check if R-square need an adjust to trust his income?
@regenerativetoday4244
4 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.
@jacintaqiu9919
6 ай бұрын
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
6 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: kzitem.info/news/bejne/rKpvxXV_amSip4I
@jacintaqiu9919
6 ай бұрын
Thank you sooooo much!!!! really helpful:)@@regenerativetoday4244
@programsolve3053
4 ай бұрын
Very well explained 🎉🎉 Thanks you so much 🎉🎉🎉
@HiralSuthar-t7i
19 күн бұрын
very good
@fariapromi4182
6 ай бұрын
Where is the dataset???
@girlthatcooks4079
9 ай бұрын
On what are you typing your codes this is not vsc?Sorry i am a begginer
@regenerativetoday4244
9 ай бұрын
This is Jupyter Notebook.
@girlthatcooks4079
9 ай бұрын
Thank you so much!
@Anand-690
2 ай бұрын
could u plz provide the Dataset being used in the video
@Puputchi
8 ай бұрын
Thank you for the tutorial!
@chiragahlawat465
3 ай бұрын
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
3 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: kzitem.info/news/bejne/zKNtl6eoroZqnXo
@chiragahlawat465
3 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!!
@subhabhadra619
Жыл бұрын
Fantastic video.simple to understand
@ceylonroadceylonroad
2 ай бұрын
hi, I'm not able to find your video on improving the R2 score. Can you show me the video? Thanks
@regenerativetoday4244
2 ай бұрын
You can watch this one that shows how to fine tune hyperparameters that should improve R2 score: kzitem.info/news/bejne/p2dpvZacpKKon6w
@PersonalOne-wn2zd
9 ай бұрын
I have a Different Insight from that i used the Wine data set for that
@fatemehrakhshanifar6402
Жыл бұрын
Hi, I could find the data but not the code, it's not on your github?
@elijahcota2408
7 ай бұрын
Thank you, god bless
@Essentialenglishwords-ii7ek
Жыл бұрын
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.
@freeprivatetutor
11 ай бұрын
excellent. very helpful. subscribed!
@tejallengare3673
Жыл бұрын
This video is very helpful thank you so much
@robinncode
5 ай бұрын
Thanks for the amazing insights!
@BasirTouati
5 ай бұрын
Please can you send me any link for case study using python polynomial regression (or multi polynomial) with data ? I want to practice.
@regenerativetoday4244
5 ай бұрын
Here it is: kzitem.info/news/bejne/z6eEynaiel-bZ6w
@KilalibaTugwell
Жыл бұрын
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.
@seifmostafa4205
3 ай бұрын
nice video, thanks for your effort ❤
@Kennerdoll
Жыл бұрын
how do i go about passing new values from a user?
@svea3524
Жыл бұрын
how do i plotthe fit line over the data?
@manyasachdeva1511
Жыл бұрын
Can you please provide the link for the csv file? I'd like to practice the codes on my own as well
@regenerativetoday4244
Жыл бұрын
Here is the link to the dataset: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/insurance.csv Thanks!
@manyasachdeva1511
Жыл бұрын
@@regenerativetoday4244 thank you so much :)
@manyasachdeva1511
Жыл бұрын
Your content is amazing
@shanenicholson94
2 жыл бұрын
Fantastic video. Very simple and to the point. How can I add the regression line to the chart?
@svea3524
Жыл бұрын
do you have the answer?
@shanenicholson94
Жыл бұрын
@@svea3524 let me find it later for you. I got it eventually
@sedativelimit
11 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')
@JyotirmoyeeRoy
5 ай бұрын
Its showing a error as "df isn't defined "
@abbddos
Жыл бұрын
Good.. but normally we test a model with data that it hasn't seen before, and that's the test split.
@maishakhatun5635
8 ай бұрын
What if a dataset has columns with numerical values but with symbols, how to do the cleaning?
@maishakhatun5635
8 ай бұрын
I mean comma or currency symbol, thank you
@maishakhatun5635
8 ай бұрын
have you got any videos that calculate the mean absolute error for evaluation?
@ThobelaGoge
5 ай бұрын
How do we access the dataset used?
@KilalibaTugwell
Жыл бұрын
This video was super helpful
@richardreneBunalos
Жыл бұрын
Can you show us how to do OneHotEncoding?
@santakmohanty612
10 ай бұрын
Could you also upload or provide a google drive link for the data set file. It would be really helpful.
@regenerativetoday4244
10 ай бұрын
Here is the link to the dataset: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/insurance.csv. I am sorry, KZitem changed their policy for links.
@santakmohanty612
10 ай бұрын
@@regenerativetoday4244 Thanks a lot !!
@subhasispaul7262
7 ай бұрын
Can you share the following data please
@tianyouhu5973
Жыл бұрын
super helpful, appreciate it
@cientifiko
Жыл бұрын
thanks... this is awesome
@nobio9591
Жыл бұрын
Thanks Dear Rashida
@BayuWicaksana95
Жыл бұрын
thank you for the tutorial
@mistymoose4424
Жыл бұрын
omg thank you queen❤
@wardaoktoh5060
9 ай бұрын
thank youuuuuuuuuuuuuuuuu miss
@sairahulreddykondlapudi8855
Жыл бұрын
training and testing on the same dataset?
@alirezarahbari3556
Жыл бұрын
Helpful🔥
@alirezarahbari3556
Жыл бұрын
Nice 👍
@3468_VAISHNAVIMUNDADA
Жыл бұрын
what to do when data have null values?
@regenerativetoday4244
Жыл бұрын
I just added a detailed video on how to deal with null values. Here is the link: kzitem.info/news/bejne/o6ScsomApKR-nag
@jayasarojam8568
7 ай бұрын
Great
@mboe94
Жыл бұрын
Why did you need to convert to category?
@regenerativetoday4244
Жыл бұрын
Because machine learning models cannot work with strings. It features and labels should be numeric
@mboe94
Жыл бұрын
@@regenerativetoday4244 Ahh, I see. Thanks for a great video!
@sheldonoumaotieno6846
Жыл бұрын
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/.
@63living.
7 ай бұрын
Can't download dataset
@regenerativetoday4244
7 ай бұрын
Here is the link: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/insurance.csv
Пікірлер: 96