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About Practice Problem: Loan Prediction III

Nothing ever becomes real till it is experienced.

-John Keats

 

While we don't know the context in which John Keats mentioned this, we are sure about its implication in data science. While you would have enjoyed and gained exposure to real world problems in this challenge, here is another opportunity to get your hand dirty with this practice problem powered by Analytics Vidhya.

 

This hackathon aims to provide a professional setup to showcase your skills and compete with their peers, learn new things and achieve a steep learning curve.

Data Science Resources

  • Are you a beginner? If yes, you can check out our latest 'Intro to Data Science' course to kickstart your journey in data science.

Rules

  • One person cannot participate with more than one user accounts.
  • You are free to use any tool and machine you have rightful access to.
  • You can use any programming language or statistical software.
  • You are free to use solution checker as many times as you want.

Registration Fee

Free
About the Loan_prediction category
Getting 0.0 score on file submission
How to apply Gradient Boosting technique on Loan Prediction hack?
How to map values using 3 columns?
Difference between train and test file
ValueError:could not convert string to float: 'Rural'
Loan Prediction Problem Dataset
Loan-prediction Practice Problem : How to improve the model?
How to impute categorical missing values?
Unable to fill missing value
Loan Prediction - Data Conversion Warning
Imputing Missing Values
Please check with the test data set, all IDs are not available
'unorderable types: str() >= float()' error in Logistic Regression
Source of Loan Prediction Data
Getting "TypeError: '>' not supported between instances of 'str' and 'float'"
How can I use "CoApplicaantIncome" as a feature?
Should target be missing in the test file?
Comparing Models Performance
Meaning of the statement : {0:.3%}".format(accuracy) in[ print "Accuracy : %s" % "{0:.3%}".format(accuracy)]
Labelencoder error
Loan Prediction III : Wanted to know about Final solution option
Confusion in replacing aggfunc by np.median() or np.mean() while using pivot table for 'LoanAmount'
I did not understand credit_history variable. Can any one help me with the explanation please?
Loan_Prediction 3 : I dont understand the 'No of Dependent' Variable
Need Help Improving Accuracy of Model
How to impute missing values for a variable like Gender?
ValueError: Unknown label type: 'unknown' for LogisticsRegression Model
Error in Final Submission of Code and CSV file
What is the hypothesis definition for this case study?
DataHackSummit 2018