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Seaborn is a visualization library for Python that builds on matplotlib and pandas. It provides beautiful default styles and color palettes for different types of plots, such as histograms, distributions, regression, and matrix plots.
Different modeling techniques like multiple linear regression and random forest, etc. will be used for predicting the cement compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy.
First of all I have uploaded a dataset from Kaggle to the Colab. Then I have imported all the necessary libraries in google colaboratory. Then I started cleaning the data and manipulate the data. After that using matplotlib and seaborn I have created some visualised graphs.