I am building a system in Python that can predict whether an object is either Rock or Mine with SONAR Data. For this use case, we are using Logistic Regression Model for our prediction.

Explain the project: I have a submarine going underwater to another country and there's a minefield for sure, and when the submarine touches the submarine it will explode. . There are also mines (rocks). The submarine must therefore predict what the obstacle is, whether it be a rock or a mine. So our mission is to create a predictable system of what is the object below the submarine is a mine or rock.

Let's do it. Since sonary is used to send sound signals and reverse review, this signal is then processed to detect whether the object (impediment) is a mine or just a rock.

Using a machine learning model, we use sonar data and our machine learning model predicts it if the body is made of metal or it's just a rock.

Work Flow:

1-Sonar Data

2-Data Preprocessing

3-Train Test Split

4-Logistic Regression Model

5-Trained Logistic Regression Model

6- Target--> Rock(R) or Mine(M)