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As an investor anyone would want to invest in people who showed a good profile of having a high probability of paying them back, proposed a machine learning model that will help them to predict this.

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Investment Predection

  • As an investor anyone would want to invest in people who showed a good profile of having a high probability of paying them back.
  • For this study I have tried to create a machine learning model that will help them to predict this.

Motivation

  • Investors are crucial part of the business, they help founders, and build business that will win the game.
  • However, an investor should invest in companies who showed a good profile of having a high probability of increasing the capital investment over a course of time.
  • And try to avoid any Ponzi scheme.

Proposed Method

  • We began the evaluation by loading the dataset.
  • Then we introduce dummy variables where needed.
  • Followed by preparing the training and test data for model.
  • The training data will be used to train the Random Forest model.
  • And the test data will be used to validate the model.

Dataset

For this project we will be exploring publicly available data from Lending Club. Lending Club connects people who need money (borrowers) with people who have money (investors).

Market Demand Of The Project

Contributing to the advancement of machine learning technologies, this project may be helpful for the investors who are looking for some good investments with calculated risks and trying to avoid any Ponzi scheme.

Future Scope

Future scope of the project includes that it can be implemented and used as a real time stock purchase prediction with further modification.

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As an investor anyone would want to invest in people who showed a good profile of having a high probability of paying them back, proposed a machine learning model that will help them to predict this.

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