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startup-analysis

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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

  • Updated Mar 18, 2025
  • Python

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

  • Updated Aug 26, 2025
  • Python

Comprehensive career analysis of 31 Indian tech companies: detailed salary data, technology stacks, interview processes, pros/cons, and strategic career guidance. Covers startups, cloud specialists, consulting firms, and niche domains with honest insights for developers at all levels.

  • Updated Feb 2, 2026

AI-powered startup analysis system using CrewAI multi-agent collaboration. Simulates a startup team with specialized Product, Engineering, and Market Research agents to evaluate business ideas.

  • Updated Jan 21, 2026
  • Python

A data mining project that analyzes startup traction data and applies various machine learning models (Logistic Regression, Decision Trees, Random Forest, XGBoost) to predict whether a startup will succeed or fail based on engagement, web presence, and social media activity.

  • Updated Sep 25, 2025
  • Jupyter Notebook

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