Project 7. Car Price Prediction using Machine Learning with Python | Machine Learning Projects

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[@kalinstanchev3602]

Благодарим ви!

[@dhanaxi_bohra1474]

your projects are good and helpful but all are without deployment. it would be very helpful if you upload 1 deployment video as well.

[@awaisahmad5908]

Great demonstration. My concepts are cleared now regarding how to fit linear regression on Such kind of datasets where there are multiple attributes like fuel kms used engine power transmission.

[@AteebTahir-z1i]

thank u best explaination on application of linear regression so far

[@kaveeshamadushan4120]

Greate explanation for learners. Thank you very much. we need more videos like this.❤

[@valeriyagamerman1415]

Thank you! Very helpful for our project.

[@Siddhardhan]

My pleasure 😇

[@AbhishekSingh-xg3zj]

Amazing explanation sir. Great video ❤

[@jamitkumar7251]

Thankyou sir, it was really helpfull ^ ^

[@fernandocorenstein6531]

Fantastic video. Thank you,

[@sakshilodhi6318]

Thank you so much for help m

[@vivekshotti]

Fantastic. Beginner Friendly. Thank you.

[@Siddhardhan]

You're most welcome!😇

[@pravin9951]

Great demonstration sir.

[@madhupincha7898]

In this tutorial we learnt regressions but how to predict price of any car when we have required parameters?

[@EcYeshwanthkumar]

Thank you for the awesome tutorial

[@vijayramchallagundla7781]

Thanks a lot for making, this video made me to get good grade in my ML subject.

[@ajayjangid4604]

why he is not used standardization in this dataset

[@shravanacharya4376]

You give a very nice explanation ..great job I hope you make more videos!!!

[@Siddhardhan]

Thank you, I will😇

[@ΑργύριοςΤακλάκογλου]

How can we change the colour of Predicted Prices in the scatter? This will help us understand better the difference between Actual Prices which will be visualized in blue colour and Predicted Prices which will be visualized in red colour.

[@DidaKusAlex]

thank you very much! finally i got it, your tutorial is awesome.

[@Siddhardhan]

Glad it helped!

[@subbaraovoleti9904]

Sir wonderful explanation.

[@mayurkoppad7871]

great work!!!

[@bhargavkongara2003]

Thank you sir

[@ashutoshshukla5344]

Thankyou!

[@pubgclutch7719]

can we use map function also right to encode the categorical to numerical?

[@clinton4817]

The Dataset Can't be accessed any more. The second time i am encountering this issue with the projects. Consider this when making your projects because i believe the projects are made to educate for a long time. Thank You

[@prateekshakatiyar4712]

It is a single variable project or a multiple variable in linear regression

[@maitreyakadam8600]

I think instead of dropping car name, it should have been used as a feature. Since some brand cars are expensive by their names.

[@Pangoangiiywb172]

Youre right dude

[@priyankchhajed9182]

😄

[@phobic1818]

Yeah I tried but it was throwing error due to strings having irregularities so we'd prolly need to process and clean the data

[@jagrutiyewale8891]

No need to remove the car_name ,just take x variable and include all parameters except name and selling prize.....

[@digigoliath]

Thanks for a newbie friendly video. I have 2 questions. 1. A newbie question. How to deploy this as a production model to predict a car price for a given set of inputs? 2. How to plot Actual Prices vs Predicted Prices in different colors?

[@Siddhardhan]

hi! you can do the deployment with flask. refer this documentation: seaborn.pydata.org/generated/seaborn.scatterplot.html to make coloured plots

[@digigoliath]

@@Siddhardhan TQVM for your quick response! Saves me time to research them.

[@Shisa58]

@@Siddhardhan Hi, I also trying to different plot colors for Actual Prices vs Predict Prices. When I tried to add hue I am getting an error. How exactly can we implement this?

[@salim_malik_vlogs]

bro, while you used lasso at end, you got test data r2 score is more compare to train data r2 score. How we can infer on this? is this overfitting or under fitting?

[@harshabijjam3262]

Thank you ..

[@sandipansarkar9211]

finished watching

[@vincetechclass3390]

Pls, how can convert binary to text?

[@ianandadk]

Actually my suggestion at 26:30, without droping those columns we can use slicing like for x = car_dataset.iloc[:, 3:] y = car_dataset.iloc[:, 2]

[@jananisubash8367]

Please explain this for me

[@jineerajkumar319]

yes but both approach gives same data in X

[@jineerajkumar319]

@@jananisubash8367 iloc is a method to select columns [ : , 3: ] means all rows but columns from 3 to last coloumn.

[@abhishekjawla1826]

superb Bhai

[@Siddhardhan]

Thank you so much bro😇

[@abhishekjawla1826]

@@Siddhardhan bro is there any project on Logistic Regression?

[@Siddhardhan]

In these 2 Projects, I have used Logistic Regression: kzbin.info/www/bejne/nJrdYoKIiad6prs kzbin.info/www/bejne/pJLGfXWarqxpoKc

[@Siddhardhan]

I'll be posting another project video on logistic regression this Friday

[@navinebhatt4014]

Shouldn't we be using one hot encoding as the encoding used assumes an order?

[@CIVILSolved]

Why you did not perform data standardization here?

[@davidagoha1236]

Thank you for the tutorial sidd. Please did anyone do this using the AWS Sagemaker model?

[@havishkahalangoda4344]

Great demonstration but how owner column become 0

[@mounikae9561]

Please make video on flight price prediction project

[@aryan-zd1cc]

how can i get the prediction to my input like how do i input my car data and check its predicted price

[@midhunkrishna902]

Hello Sir, I'm student of BCA Data Science. I really liked this project. Such a great efforts Sir Can you please provide it's Documentation Sir?

[@midhunkrishna902]

Data Collection and Preprocessing Feature of Engineering and Selection Model Selection and Evaluation Model training and testing Result and analysis Conclusion

[@nagusameta366]

Would it be beneficial to perform one-hot encoding on the categorical features that have more than 2 categories (e.g. 0, 1, 2...)? It was suggested in a different lecture, but i dont know what to do then if the number of categories go higher like 10 or more.

[@LoneWolf-rj1px]

For this case, I do not think it would be beneficial as it will increase memory consumption. What I am concerned about is whether should we use a standard scaler here.

[@nagusameta366]

@@LoneWolf-rj1px Thanks for the insight!

[@kumarabhinandan840]

For more than 3 categories go with one hot encoding and for less go with label encoding

[@zhironggu-j1m]

what should i do if isnull().sum() is not none? do you have video to solve it?

[@Al-khayr.2002]

I clicked on the link to the dataset in the description I am getting a 404 page not found error Any help please

[@user-ps9mk3pi7o]

Where did you get the dataset from

[@tonymathewjohn5958]

super class

[@Thandi899]

Thank you for informative video. Why didn't you use dummy variables instead of manually doing it yourself? Is it just a preference or there are advantages to it?

[@Siddhardhan]

hi! thanks for your positive words 😇 it's just my preference... you can definitely try that out.

[@Thandi899]

@@Siddhardhan oh okay, awesome. May you please assist me with writing a function that; - Takes in a dataframe (df), - Standardize the features using StandardScaler() - Split data into 25% training, random_state =25% - Fills any NAN values with zero. I’m able to do it step by step but not as one function

[@strongsyedaa7378]

@@Siddhardhan Can KNN be used on this dataset? As Dataset be divided into k folds so which model to be chosen?

[@simonishabiyi]

the dataset isnt available can you pls hlp by making it available

[@crazyfootball2753]

to test the validity of model beyond r2 score if we specify attribute values that are closer to one of the training data record, in the final output window, should the model need to predict the price nearer to selling price for that specific record in training data? Expecting your answers. Thanks

[@satyamshaw2280]

sir dataset is not opening

[@manuthvann7560]

Thanks for making this impressive vdo tutorial alot, sir . I am now working on this project for my school assignment, but since I am a newbie to ML. I am wondering whether there is any possible way to make damaged car identification using machine learning, also it can predict, what status our cars are in ( good, new, .. ) and if good how many percentages. Looking forward to hearing back from you thanks

[@vibetrendzz]

Can I have your report of this program

[@ayushdubey3550]

@@vibetrendzz Can I get your report?

[@jillurrahman6913]

dataset is not found

[@ninadekbote6652]

How many iterations?

[@adhiwirahardi]

where you get the data set

[@badrimunaganti5363]

How can we find the accuracy for this sir.

[@ekaagustina9010]

33:55 the Rsquared. When do we use this? Is it because using linear model? is it only for linear model? is there any spesific reason sir on when exactly we use this metrics?

[@Siddhardhan]

we use it for Regression models.

[@tanubhawsar1714]

@siddhardhan can you please share the report of this project

[@rajeshkapase9046]

how i can get data for cost prediction model for edtech firm using maching learning

[@garv18x]

can this project work with api ?

[@mukundbharadwajL]

isnt car name also categorical value?

[@raunak3406]

if r squared error is more for lasso how is it better than linear?

[@lakshmireddyperam6377]

Why you skip EDA part you just take a simple dataset and applying a ml algorithem its better to add EDA part for better understanding

[@abhishekpanjiyar8266]

how can we plot a line in linier regression model and how can we write the difference in selling price in actual and predicted value

[@Siddhardhan]

hi! you can try and.lmplot() from seaborn to plot linear model with your data. Refer seaborn documentation on how to do this. we can find the difference of the actual price & predicted price with metrics like mean absolute error, etc.

[@abhishekpanjiyar8266]

@@Siddhardhan ok thanks,did both of it,but how this model worked behind ,which feature(column) have been given how much importance,for predicting selling price,please suggest best book for maths for machine learning,i am new to this field

[@Motivation_Shorts-m]

I am having an error after I'm using the fit function for the training data. Could you please tell me how to fix this error

[@SZS154]

same did u find out?

[@Yash-yl7vg]

At 32:00 erro is coming "could not convert string to float: LPG"

[@Siddhardhan]

hi! mail your Colab file link to [e-mail]

[@Yash-yl7vg]

@@Siddhardhan ok sir thankyou for replying so quick

[@anilkumarreddyreddy6311]

@@Siddhardhan Am getting error Could not convert string to float:CNG

[@bhavyav8355]

Here ,what is the purpose of importing seaborn ?

[@Siddhardhan]

seaborn is used for plotting the data

[@VarshiniR-gd8qv]

Bro can I get car price prediction with python in deep learning

[@BRISHTIDAS-o4b]

cant understand why are you using lasso regression

[@habteroyal9444]

how to download data set???

[@ayubcade5248]

What is the problem and why to predict i don't understand😑

[@hajaksksnsjksksbsnsn]

I have confusion on using same dataset for training and prediction. I think you should use test dataset for prediction instead of training dataset i.e. X_train. Please clarify my doubt.

[@Siddhardhan]

hi! the reason for finding the accuracy on x_train and x_test is to determine whether the model has overtrained. that's the reason why I used x_train as well.

[@hajaksksnsjksksbsnsn]

@@Siddhardhan ok. But what should be the correct approach for real time scenario?

[@ancytech8186]

Bro , How can we contact you personally ? Can you work for my An AI project ?

[@Siddhardhan]

hi! I am sorry. I don't work on freelance projects as of now.

[@ancytech8186]

@@Siddhardhan We are recruiting people for an AI startup . So We hope you can guide us technically .

[@nibin7]

Superb work! Splitting the data into train and test---Even after spelling correctly, I get an error "the column not found in axis'' Can I replace data.drop with data.iloc for all cases.

[@Siddhardhan]

hi! share the details of the error with your Colab file link to [e-mail]

[@abhinavkale4632]

you have to mention axis = 1 inside the drop function along with the column function

[@nomoregamesfacts123]

Iam getting error at linear regression model can anyone help me

[@pesallway]

Sir Can I Keep this sort of Projects in Resume with just this notebook implementation

[@Siddhardhan]

you can add few more things like optimization, deployment, etc

[@pesallway]

@@Siddhardhan is it enough If I just make a model in Jupiter notebook..as I don't enough time further steps like deployment as I want to include atleast one project in ML in my resume...is it enough sir

[@Siddhardhan]

I am not sure. It won't be sufficient if you ask me.

[@pesallway]

@@Siddhardhan okay sir

[@khaledabunada3506]

عمل رائع

[@Siddhardhan]

Thanks 😇

[@shirshchauhan4429]

how to find 12. Which is the most and least cost depreciated vehicle in data ? 13. Which brands of vehicles are less affected by cost depreciation ? 14. Can we get idea about newest vehicles i.e. after 2014 manufactured ? 15. Can we find out data of only two wheelers from this data? pls answer this fast pls

[@vinodhm3369]

You have to find the values from the data by doing some calculations

[@9881847751]

why i am Founding input variables with inconsistent numbers of samples: [301, 1]

[@9881847751]

by doing in train_test_split

[@haleemasadia9743]

Is there any video on features extraction?

[@Siddhardhan]

Hi! I'll be posting a video on feature extraction of text data this Wednesday. You can watch this project video. I have explained how to convert text to feature vectors. (Fake News Prediction) : kzbin.info/www/bejne/pJLGfXWarqxpoKc

[@haleemasadia9743]

@@Siddhardhan can you provide me your contact details please

[@AdilKhan-lz2ch]

Would it be possible to reach out to you privately for assistance? Please share your info if you are available for help.

[@Siddhardhan]

hi! send a mail to [e-mail]

[@ajaykushwaha-je6mw]

you have done ordinal encoding for fuel type: this approach is wrong.

[@adnanabdullah2239]

When we print(car_dataset.Fuel_Type.value_counts()), it shows Name: Fuel_Type, dtype: int64. Does this int64 imply no. of counts? (As Fuel_Type column contains, string type data, I got confused)

[@Siddhardhan]

yes, it is.

[@samadhanpawar6554]

In real world how to predict price without car name

[@ayushdubey3550]

If anyone here has made a project on this topic, Can you share your project file??

[@thecampfire1094]

Bhaiya can i use this as Final Year projects ?? If Notchoose suggest another machine leanring topic Congrats you got new subscriber

[@Siddhardhan]

hi! I am not sure whether it would be approved. you may go with deep learning Projects.

[@shansingh9858]

Hey camp fire...this project will be good for complete beginners but at least build some real time projects..

[@9881847751]

The data show parsererror : expected 3 field in line 43,saw 5 😭😭😭

[@Siddhardhan]

download this dataset file instead: drive.google.com/file/d/1TCZdOO7AXHZ0ZN0eJHbwmWP6dtMTNFde/view?usp=drivesdk

[@9881847751]

@@Siddhardhan thanks man🤓

[@ruchitachauhan6546]

Actual price to nikali hi nhi

[@sandeshbhurtyal9150]

lol

[@surbhitpratik]

While writing the encoding of data using replace function, I'm getting an error "TypeError: Cannot compare types 'ndarray(dtype=int64)' and 'str' ", so I'm not able to change my values to 0,1 & 2.

[@sudhanshusingh5594]

The reason for this error is because of the number of times you execute the cell. The first time you execute the cell the transformation happens ('Y' -> 1, and 'N' -> 0). At this point if you try to rerun the same cell, the data type for physicalEvidence and contact is now an int rather than a string. So when the replace method runs, it is look for a 'Y' or 'N', but DOES NOT find any because all of the values have been replaced with 1 or 0. If this happens, you'll just need to reload the dataframe (df) again and rerun the cell one time. I hope this helps! Let me know your thoughts.