An interactive machine learning and data visualization project

This project uses machine learning to predict the success of startup companies based on various features such as funding, location, industry, and team size. The goal is to help investors and entrepreneurs make more informed decisions about which startups to invest in or launch or the startup will be successfull or not.

Exploratory Data Analysis and Prediction on Indian Startup Funding dataset using Python

Analysis of information about startup companies done using machine learning and data analytics methods to predict the success of the startup companies.

Building a model to predict startup success rate

This is my final year project for this project I have used crunchbase dataset

Unicorn Prediction and Startup-Investor Recommendation System

It is a web application for Venture Capitalist which predicts the success of startup companies to ease the decision whether to invest in the startup or not.

Indian Startup Ecosystem Analysis & Funding Predictor An interactive dashboard with ML-powered funding prediction for analyzing the Indian startup landscape (2018-2020).

The aim of the project is to predicting the whether the Startups are success or failure using supervised learning and using some hypothesis-testing techniques to validate the project.

Start-Up Success Prediction With Tuning Parameter

prediction analytics of startup success

A startup or start-up is a company or project begun by an entrepreneur to seek, develop, and validate a scalable economic model. While entrepreneurship refers to all new businesses, including self-employment and businesses that never intend to become registered, startups refer to new businesses that intend to grow large beyond the solo founder. Startups face high uncertainty and have high rates of failure, but a minority of them do go on to be successful and influential. Some startups become unicorns: privately held startup companies valued at over US$1 billion. [Source of information: Wikipedia]

This project predicts startup profitability using Logistic Regression and Random Forest, analysing financial (funding amount, funding rounds, revenue), market (market share), and operational (startup age, employee count) factors. It evaluates AUC, accuracy, precision, recall, and F1-score, addressing underfitting, overfitting, and feature selection

Startup Profit Prediction Interface using Django / 50_Startups.csv

A Multi-Model AI Pipeline for Startup predictions

ASSIGNMENT FOR BATCH 2 Apply where it is necessary i:e data preprocessing,linear regression ,polynomial regression, and decision tree etc on the following data-set and compare the accuracy of all regression and take screenshots of output prediction and accuracy of all the regression which you are going to apply and upload all the codes on github with screenshot.Dont try to copy others because we give you just half data-set and when you show us output for future analysis we will compare your values with the remaining half of the data-set and then give you marks. Explanation of the data-set is as follows: 1. Take 50 startups of two countries and find out which country is going to provide best profit in future. 2. Annual temperature between two industries is given. Predict the temperature in 2016 and 2017 using the past data of both country. 3. Data of global production of CO2 of a place is given between 1970s to 2010. Predict the CO2 production for the years 2011, 2012 and 2013 using the old data set. 4. Housing price according to the ID is assigned to every-house. Perform future analysis where when ID is inserted the housing price is displayed. 5. Data of monthly experience and income distribution of different employs is given. Perform regression.

Startup prediction system with django and react

Web based startup success prediction system

More and more institutions, governments, and private organizations are investing in these companies and encouraging people to use them to explore their ideas. Companies can easily raise millions of dollars and reach unicorn status in just a few years.

Predicting startup profit using regression models and data analysis

Predicting startup performance using data analytics to support venture capital investment decisions

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Profit Prediction for 50 Startup depends on the money have to spent in the R&D department,Marketing department and the state and improve our ML model using backward elimination technique to select the approporaite features

Machine Learning Final Project - Startup Success Prediction

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I will be predicting the profit from the startup’s dataset with the features available . I'm using the 50-startups dataset for this problem statement and I will be using the concept of Multiple linear regression to predict the profit of startups companies.

practice 2.1 | multilinear regression | startup companies | profit prediction

Analysis and Prediction of the Success Rate of Startups