The problem of predicting concrete compression strength, vital for ensuring the safety and durability of civil engineering structures, was first addressed by Prof. I-Cheng Yeh in 2007, building on his 1998 research. This project, using Yeh's dataset, aims to optimize concrete performance by exploring the effects of ingredient concentrations and testing age on compression strength. By applying advanced machine learning techniques, the goal is to create a predictive model that improves accuracy and provides insights into the factors influencing concrete strength, ultimately enhancing material design and construction practices.

This LBB is used to learn about Machine Learning Classification I by using the data's about Titanic Passenger and predicting wether they would survive or not

This Analysis is created with the goal of learning Linear Regression while also seeing the variables that affects a companies profits