House Price Prediction Project | Linear Regression | Machine Learning

Hey everyone,
This video covers a Linear Regression project of `House Price Prediction`.
Here I have explained the code for the same in detailed way.
Code : github.com/Ris...
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/ insightsbyrish
#linearregression
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#computerscience
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[@InsightsByRish]

Correction : At 12:08 upper bound = Q3 + 1.5 * IQR

[@hriupadhyay5763]

Please provide me a link for this particular data set

[@ilyeskesri6524]

Good tutorial thanks

[@ansumankumar4797]

Very nice explanation.

[@InsightsByRish]

Thank you. Pleased to know you liked the content.

[@ibrahimnazari8376]

nice explanation, thanks

[@Luminouss12096]

from sklearn.linear_model import LinearRegression model = LinearRegression() model.fit(X_train, y_train) mam this part of code show error how can i solve this

[@InsightsByRish]

What's the error?

[@Luminouss12096]

@@InsightsByRish model.fit(X_train, y_train) Input X contains NaN. LinearRegression does not accept missing values encoded as NaN natively. For supervised learning, you might want to consider sklearn.ensemble.HistGradientBoostingClassifier and Regressor which accept missing values encoded as NaNs natively. Alternatively, it is possible to preprocess the data, for instance by using an imputer transformer in a pipeline or drop samples with missing values.

[@InsightsByRish]

​@@Luminouss12096 I think your input data frame (X) still consist of missing values. Try removing that before building the model. If you still encounter the error then mail your .ipynb file on [e-mail].

[@hriupadhyay5763]

Can you please provide a link for this particular data set please

[@InsightsByRish]

Hey, I've provided the GitHub repository link in description box. Dataset is available there.

[@alaa_abdestar]

kaggle dataset link plz??

[@InsightsByRish]

I downloaded the dataset from GeeksforGeeks : media.geeksforgeeks.org/wp-content/uploads/20240905183434/HousePricePrediction.xlsx

[@jaisiddhisuperpowerpltd1872]

mam , are you indian or foreigner

[@omkarcode]

I think It's not correct lowerBound = Q1 - 1.5 * IQR upperBound = Q1 + 1.5 * IQR Correct lowerBound = Q1 - 1.5 * IQR upperBound = Q3 + 1.5 * IQR

[@InsightsByRish]

Yes, it should be Q3. I've mistakenly considered it as Q1.

[@flavourlyfreshasmr151]

Can you explain, how you remove columns and rows from the original dataset, logic?

[@InsightsByRish]

Logic is the columns that don't help us in any way for making predictions are removed. Like the User ID column which has zero correlation with the target column. And for rows they are either removed if they contain null values or outliers.

[@flavourlyfreshasmr151]

@@InsightsByRish can you make separate video to discuss which features we have to take and which should remove , in our particular problem statement.you r videos are so helpful

[@InsightsByRish]

Thank you! Will make one on that topic soon.

[@flavourlyfreshasmr151]

@@InsightsByRish Great 👍

[@akshit_trivedi]

Can you please make a playlist of all projects?

[@InsightsByRish]

Yes sure..!

[@MuhammadEhtisham-cm5vr]

plz make a seperate videos for feature engineering and scaling

[@InsightsByRish]

Ok, will make soon.

[@green_valley_farms]

can you please share the code

[@InsightsByRish]

Hey, I have provided the link of GitHub repository for the code in the description box.

[@vikashsingh6888]

It shows an error when I select_datatype('object') and when I change it to int then my column size changes please help 🙏 At line 27

[@InsightsByRish]

It's not select_datatype('object'). It is select_dtypes('object').

[@vikashsingh6888]

Yes I tried this one also but it's showing issue... While I run the encoder it shows an error that you have to select int or str

[@vikashsingh6888]

I tried it also but it's showing error while I run the encoder part its showing an error that you should select int or str in encoder.fit(df[cat_col])​ @@InsightsByRish

[@InsightsByRish]

@@vikashsingh6888 Hey, not really able to understand what's going wrong with your code, but I would suggest that restart your kernel and again implement the code from beginning line by line as it is (I've provided the code on GitHub).

[@vikashsingh6888]

If you will provide your insta or something for contact even email I will send you the ss .. if you can it will help me 🙏