https://github.com/abdul-aa/shark-tank-pitches

Predictive Modeling and Clustering Insights for Success on Shark Tank
https://github.com/abdul-aa/shark-tank-pitches

bagging-ensemble boosting-algorithms cluster-analysis clustering data-visualization ggplot2 kmeans-clustering r-programming

Last synced: about 2 months ago
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Predictive Modeling and Clustering Insights for Success on Shark Tank

• Host: GitHub
• URL: https://github.com/abdul-aa/shark-tank-pitches
• Owner: Abdul-AA
• License: mit
• Created: 2023-12-04T13:56:39.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-02-15T02:51:44.000Z (11 months ago)
• Last Synced: 2024-02-15T03:34:14.633Z (11 months ago)
• Topics: bagging-ensemble, boosting-algorithms, cluster-analysis, clustering, data-visualization, ggplot2, kmeans-clustering, r-programming
• Language: R
• Homepage:
• Size: 1.26 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Shark-Tank-Pitches

## Context

Navigating the realm of innovative business ideas is a daunting task, with the elusive nature of groundbreaking

concepts. This challenge is vividly illustrated on the popular platform, Shark Tank, where

aspiring entrepreneurs present their ventures to a panel of investors, known as Sharks. The dynamic

involves negotiating a deal, often involving relinquishing a percentage of their business in exchange for

financial backing and the invaluable mentorship, connections, and expertise of the Sharks. The highstakes

nature of these negotiations compels the Sharks to meticulously scrutinize business profits, records,

and performance, aiming to validate the purported valuation of the business. 

Recognizing the intricacies

involved in this venture underscores the potential value of a predictive model capable of accurately

forecasting whether a business can secure a deal. Moreover, the insights gleaned from previous pitches

can empower entrepreneurs, offering them a strategic advantage in positioning themselves for success

while optimizing their use of time and resources.This project aims to develop a classification model to

predict business success on the platform, while also conducting exploratory data analysis and clustering

to extract actionable insights from past pitches, thereby providing a valuable resource for aspiring

entrepreneurs.

[Full Report](https://github.com/Abdul-AA/Shark-Tank-Pitches/blob/6d7a08b1fa0fdc35d6b1ae38de1a47a97cdbb259/Project%20Report.pdf)