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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

  • You can refer our learning path to learn more about the tools and technologies required to solve Data science problems. You can find it here.
  • You can participate in workshop "Experiments with Data" to start your data science journey using Excel, R or Python
  • Data Exploration is the core of machine learning competition. To understand more about it, click here.
  • You can refer introduction course to participate in machine learning competition on DataCamp designed by Analytics Vidhya.


  • 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.

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About the Loan_prediction category
'unorderable types: str() >= float()' error in Logistic Regression
Getting 0.0 score on file submission
How to map values using 3 columns?
Please check with the test data set, all IDs are not available
Loan Prediction Problem Dataset
Source of Loan Prediction Data
Getting "TypeError: '>' not supported between instances of 'str' and 'float'"
How can I use "CoApplicaantIncome" as a feature?
Imputing Missing Values
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?
Loan Prediction 3: Reveal Your Approach
How to check accuracy of Logistic Regression model
Loan-prediction Practice Problem : How to improve the model?
Changing categorial into numerical variables
Object dtype instead of float
Filling missing values
Can i download test result for datahack>