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Machine learning model which can predict the strength of a mixture for given composition of ingredients like cement, slag, ash, water, superplastic, coarse aggregates, fine aggregates, age.

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Varun-N-M/strength-of-concrete_using_ML_models

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strength-of-concrete_using_ML_models

Name of project

Capstone project - Concrete data

Tool used for analysis

• Python

Packages

• NumPy

• Pandas

• Matplotlib

• Seaborn

• scikit-learn

Data: https://www.kaggle.com/datasets/niteshyadav3103/concrete-compressive-strength

Analysis:

• We have 1030 rows

• We have 9 columns

• There is no null values

• All values are in the form of continuous data

Further process of

• Exploratory data analysis

• Outliers treatment

• Relation study

• Multi-collinearity-check

• Feature Engineering

• Model building

• Hyperparameter tuning

are explained in construction_data_report.

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Machine learning model which can predict the strength of a mixture for given composition of ingredients like cement, slag, ash, water, superplastic, coarse aggregates, fine aggregates, age.

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