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50_Startups.csv
50_Startups.csv
 
 
README.md
README.md
 
 
Startup_Profit_Prediction.ipynb
Startup_Profit_Prediction.ipynb
 
 

README.md

Startup Profit Prediction

GOAL

The goal of this project is to analyse and predict profit of a startup from features as 'R&D Spend', 'Administration', 'Marketing Spend', 'State' etc.

DATASET

Dataset can be downloaded from here.

WHAT I HAD DONE

  • Step 1: Data Exploration
  • Step 2: Data Preparation
  • Step 3: Data Training
  • Step 4: Model Creation
  • Step 5: Performance Check

MODELS USED

  • Linear Regression
  • Lasso Regression
  • Ridge Regression

LIBRARIES NEEDED

  • pandas
  • numpy
  • sklearn (For data training, importing models and performance check)

Accuracy of different models used

  • By using Linear Regression model
   Accuracy achieved :  94.87
  • By using Lasso Regression model
   Accuracy achieved :  94.87
  • By using Ridge Regression model
   Accuracy achieved :  94.87

CONCLUSION

  • All 3 regression algorithms used in this project are equally efficient for the given dataset.
  • RMSE for Ridge Regression is least

Author

Ayushi Shrivastava