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car-price-prediction's Introduction

Car-Price-Prediction

car-price-prediction's People

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mayurg6832 mdjawad006 iamsantoshkumar vuradimani asalimahmed prawinrajae rushikeshn19 akashpatil327 rahul1984 sketchjar surajit112 subashcj7 yogeshkumar1999 shaheer-akun pramodswainn raghavsharma0007 swati-thapa anilboppana murtuza10 rizwannitk ravi-a-patel crazyphoton007 sekharpink1 umair1234-dotcom mayankkyogi abhinavtiwari123 samuel-anbudaiyan zshivaay aringholap vasu081098 sandhya1825 sankethv agentnik rupesh-987 sreejithstat bimalmaan n-varshney ashishbhagchandani karkerayashish shaikhf1986 tbirdss mdmonsurali kev-kutkin abhishekvickyvyas arjunpukale kesava333 nidhi988 datascience-vishal akshit113 kishankumar09ei sudh284 veda1612 benspniz hemantdm singhhari842 badal244 yashwanth-gurram jaymilanson1682 koustavbiswas souvikr33 bhushan1002 sarthaktwr madhudugyala rajajrds subidita-262 sushil-ms abhisheksurya578 aakriti1318 aquaman001 inspirahul prep-jnani sravanthishoroff pratapakhand rahulvrmec sudharsan203 vidyamcode sakibapon amankumar-144 adnan64-hub saurabhxgill tannypartner amarjeet-cheema aravind-naidu saragadamraviteja surendrakumar422 narendra281 swapnil110399 neurochenyin yunu100 anjani-1999 madhuri777289 mahaprathamesh sanjay-code-creator rdshyamvijay navya-manya mohammedaz33m vrinda518 ankitjoshi1995 zianafique yashkumar26

car-price-prediction's Issues

For Prediction use Kms_Driven instead of its log(i.e. Kms_driven2) as we have trained the model using Kms_Driven

When predicting use 'Kms_Driven' instead of its log(i.e. 'Kms_driven2') as we have trained the model using 'Kms_Driven' feature.

Ref :

Car-Price-Prediction/app.py

Line 43 in f9540e9

 prediction=model.predict([[Present_Price,Kms_Driven2,Owner,Year,Fuel_Type_Diesel,Fuel_Type_Petrol,Seller_Type_Individual,Transmission_Mannual]]) 

In line 90, it shows an error: "NameError: name 'plt' is not defined"

This can be fixed by importing matplotlib at the beginning of the code block.
"import matplotlib.pyplot as plt"

Error running the app.py file

I m getting this error message any idea on how to resolve this?

Add README for Car Price Prediction

I noticed that there is no README file in the repository, and I'd like to contribute by adding one for better project understanding and onboarding. I plan to include sections on project overview, setup instructions, and usage guidelines. If there are specific details or preferences, please let me know. Looking forward to your guidance!

AttributeError: '_io.BufferedWriter' object has no attribute 'predict'

I have received an error while running the code

after submitting the requested info

prediction = model.predict([[Present_Price, Kms_Driven, Owner, Year, Fuel_Type_Diesel, Fuel_Type_Petrol,
AttributeError: '_io.BufferedWriter' object has no attribute 'predict'

ValueError

Hi Sir,
Thanks for conducting Live session of End-to-End project implementation, It was very helpful in learning project implementation,
but I've been facing ValueError
"ValueError: Number of features of the model must match the input. Model n_features is 9 and input n_features is 8"
File "/Users/shaheer/ML projects/app.py", line 46, in predict
prediction=model.predict([[Present_Price,Kms_Driven2,Owner,Year,Fuel_Type_Diesel,Fuel_Type_Petrol,Seller_Type_Individual,Transmission_Mannual]])
kindly review this issue and suggest fix,

Thank you.

AttributeError: type object 'dict' has no attribute 'predict'

I have received an error while running the code

after submitting the requested info:

prediction = model.predict([[Present_Price, Kms_Driven, Owner, Year, Fuel_Type_Diesel,
Fuel_Type_Petrol, Seller_Type_Individual, Transmission_Mannual]])

not using any data pipelines

there are no data pipelines to make the data flow automated. if this project deployed in cloud and if there is extra data to be trained how would you do that ?

delete main.py

The file app.py is doing the same work as main.py we can delete it

Fuel_Type 'CNG' should be handled

Ref :

Car-Price-Prediction/app.py

Lines 26 to 31 in f9540e9

 if(Fuel_Type_Petrol=='Petrol'): 

 Fuel_Type_Petrol=1 

 Fuel_Type_Diesel=0 

 else: 

 Fuel_Type_Petrol=0 

 Fuel_Type_Diesel=1

'CNG' fuel type must be handled as the training and test data has those samples as well
Following code resolves the issue:
if(Fuel_Type_Petrol=='Petrol'):
Fuel_Type_Petrol=1
Fuel_Type_Diesel=0
elif(Fuel_Type_Petrol=='Diesel'):
Fuel_Type_Petrol=0
Fuel_Type_Diesel=1
else: # Fuel Type is CNG
Fuel_Type_Petrol = 0
Fuel_Type_Diesel = 0

	if(Fuel_Type_Petrol=='Petrol'):
	Fuel_Type_Petrol=1
	Fuel_Type_Diesel=0
	else:
	Fuel_Type_Petrol=0
	Fuel_Type_Diesel=1