Skip to content

Given dataset of Diamonds with features such as Cut, Carat, Clarity etc. I have used libraries such as Pandas, Numpy, Matplotlib, Seaborn to Analyse and Estimate the Price of Diamonds based on the features. Using Scikit-Learn , implemented Algorithms to increase the effective R2 score.

License

Notifications You must be signed in to change notification settings

Chinmayrane16/Diamonds-In-Depth-Analysis

Repository files navigation

Diamonds-In-Depth-Analysis

Diamonds

  • Given dataset of Diamonds with features such as Cut, Carat, Clarity etc.
  • I have used Libraries such as Pandas, Numpy, Matplotlib, Seaborn to Analyse and Estimate the Price of Diamonds based on the features.
  • Used Scikit-Learn to implement Regression models to improve the R2 Score.
  • Analyzed and Visualized both the distribution of Categorical and Numerical Features.
  • Used StandardScaler to Scale the numerical values.
  • Finally, I have Tuned the Parameters with the help of GridSearchCV.

About

Given dataset of Diamonds with features such as Cut, Carat, Clarity etc. I have used libraries such as Pandas, Numpy, Matplotlib, Seaborn to Analyse and Estimate the Price of Diamonds based on the features. Using Scikit-Learn , implemented Algorithms to increase the effective R2 score.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published