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.

This project uses a dataset of over 1000 concrete samples with 9 predictor variables and tries to predict the strength using a neural network in keras. The model uses 1 hidden layer with 10 nodes, a ReLU activation function with ADAM optimizer, and trains the data using 50 epochs then 100 epochs and then 3 hidden layers.

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

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

A jupyter notebook with a python script for predicting the strength of concrete test cubes at 28 days given any age before then, and two additional parameters.

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

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

Development of an AutoML System to Predict the Compressive Strength of Concrete