page-header

Concrete Strength Prediction

Project Description

For many of us, concrete is that thing used to make our pavements, which is why it is so very important to test its strength.

In this dataset, I analysed 8 features including concrete, ash and water. This required some domain knowledge to know what actually gives concrete its strength.

I then created multiple models and ran K-fold validation on each one in order to improve the results. I then tuned the parameters of the model I chose, with Random Search and Grid Search. I also applied some feature engineering techniques in order to enhance the model.

Photo credit : Cor-Tuf

  • This notebook is not available publicly due to course rules.

    Client: AIML Program at University of Texas, delivered online by Great Learning

    Skills: Supervised Learning (Regression), EDA, Feature Engineering, Grid Search and Random Search