Revisiting_a_Concrete_Strength_Machine_Learning_and_Data_Analysis

dataset downloaded from Kaggle website, and notebook will be upload there.

Data Set Information:

Number of instances 1030
Number of Attributes 9
Attribute breakdown 8 quantitative input variables, and 1 quantitative output variable
Missing Attribute Values None

Attribute Information:

Given are the variable name, variable type, the measurement unit and a brief description. The concrete compressive strength is the regression problem. The order of this listing corresponds to the order of numerals along the rows of the database.

Name -- Data Type -- Measurement -- Description

• Cement (component 1) -- quantitative -- kg in a m3 mixture -- Input Variable
• Blast Furnace Slag (component 2) -- quantitative -- kg in a m3 mixture -- Input Variable
• Fly Ash (component 3) -- quantitative -- kg in a m3 mixture -- Input Variable
• Water (component 4) -- quantitative -- kg in a m3 mixture -- Input Variable
• Superplasticizer (component 5) -- quantitative -- kg in a m3 mixture -- Input Variable
• Coarse Aggregate (component 6) -- quantitative -- kg in a m3 mixture -- Input Variable
• Fine Aggregate (component 7) -- quantitative -- kg in a m3 mixture -- Input Variable
• Age -- quantitative -- Day (1~365) -- Input Variable
• Concrete compressive strength -- quantitative -- MPa -- Output Variable

Inspiration

Can you predict the strength of concrete? ** for more information and model prediction figures please visit jupyter notebook.