Project ,

Loan Granting and Status Prediction

In this project, you will study the bank’s data and create a machine learning model that can determine whether or not to grant the loan based on the livelihood of the loan being repaid.

What will you Learn in the Project?

As part of this project you will learn following:

  1. Data loading and data pre-processing
  2. Data munging
  3. How to visualize data using matplotlib and seaborn
  4. Machine learning algorithms – Logistic Regression and Random Forest
  5. Bagging and boosting methods

Tools Used

  1. Jupyter Notebook
  2. Numpy
  3. Pandas
  4. Scikit learn
  5. Matplotlib,Seaborn and folium

Tasks Performed

As part of this project we will be performing following tasks:

Task-1 : Data loading and Exploratory Data Analysis

Task-2 : Split the data into training and testing Model building using Random forest and logistic regression

Task-3 : Build bagging and boosting to increase the performance

 Task-4 : Calculate the out of bag error for the random forest algorithm to check the accuracy error of the model and also generate its graph

+4 enrolled
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or 99₹ 999
91% off

Skills you will develop

Data loading and data pre-processing

Data munging

Visualize data with Matplotlib


Logistic Regression

Random Forest

Bagging and boosting methods

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