concrete-strength

Analysing the concrete dataset from I-Cheng Yeh (1998) with Python, scikit-learn, Bokeh

Concrete compressive strength prediction with machine learning using the R Caret package.

Concrete Strength Estimator is a modern Next.js web dashboard that allows users to adjust 15 distinct mix parameters and instantly see the predicted compressive strength (in MPa).

Feature Engineering on Concrete Strength prediction using Machine Learning Techniques in Python

Compare Machine Learning and Artificial Intelligence models for predicting concrete compressive strength — featuring a Tkinter GUI, TensorFlow/Keras AI, Scikit-learn ML, and SQLite integration.

A Hybrid Physics-Informed Machine Learning (PIML) System for Iraqi Concrete Optimization. Integrating DoE, Transfer Learning, and Lean Six Sigma for Engineering Certainty. [Phase 1: EDA]

Concrete strength prediction based on its composition and curing process using CatBoost, XGBoost and LGBM.

My projects and practices on various segments of machine learning and deep learning.

Tabular presentation of concrete strength

Microsoft Student Accelerator 2020: Predicting Concrete Strength with Artificial Neural Networks

Predict concrete compressive strength using an artificial neural network (ANN).

A python program that uses Neural Network to predict strength of given samples of concrete.

Reproducible datasets, computational workflows, and model implementations for externally validated tabular foundation models and explainable concrete compressive strength prediction.

Predicting concrete compressive strength using regression-based machine learning models.