Abstract

According to experts, 90 out of 100 Startups fail within the first year of their launch. There are several reasons behind that but one of the very first and major reasons is Idea Validation. The Entrepreneurs are so excited about their idea that they forget about this very important step, which fails the Startup. Startup Idea Validation tool provides the entrepreneurs with a roadmap by asking the right questions relevant to their ideas and providing suggestions and improvements based on the inputs provided by the User. We are using Linear Regression and Support Vector Machine to train the machine on the Expert Dataset provided and we conclude the result based on that. With this, we’ll be able to train the machine with an accuracy of up to 99.99%. There are no other tools available so far which can validate a Startup idea automatically. This tool can be a great breakthrough in the field of Startups.

Highlights

  • For almost more than a decade Startup has been a burning topic among the Engineers, Students

  • According to one of the articles on cbinsights.com, the number one reason for the failure of a Startup is- No Market Need and along with that there are 19 other major reasons they have mentioned like Funding, Team, Competition, Pricing and so on

  • There can be many ideas that need to validate. To solve this problem and save the founders some time, we are creating a startup Idea validation tool using machine learning which will provide the founders with the right feedback on which they can work and either stop or continue the venture based on that

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Summary

INTRODUCTION

For almost more than a decade Startup has been a burning topic among the Engineers, Students. That is where the Idea validation software comes in the picture.Currently, it is being done manually by some industry experts and they charge for it. We will be validating the idea with the help of Artificial Intelligence and Machine Learning.

LITERATURE SURVEY
PROBLEM DEFINITION AND SCOPE
PROPOSED ALGORITHM
Encoding
Support Vector Regression(SVR)
Linear Regression
IMPLEMENTATION
CONCLUSION AND FUTURE WORK
EXPERIMENT AND RESULT
Findings
Benjamin

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