SONAR is an abbreviation for Sound Navigation and Ranging. It detects submerged things using sound waves. Deep learning and machine learning-based techniques have applications in recognizing sonar sounds and hence targets.
Fourier transform, wavelet transform, limit cycle, etc. are signal processing methods applicable for an underwater acoustic signal. Machine Learning enables the processing of sonar signals and target detection. It is a subfield of artificial intelligence which tells machines how to manipulate data more proficiently. The three stages of Machine Learning are taking some data as input, extracting features, and predicting new patterns.
We will explore rock vs. mine prediction using logistic regression in Python programming using scikit-learn.
The objective of this project is to whenever there is a war between two countries one country will use a submarine for war on the other country and the other country will keep explosives on the ocean to predict whether it is rock or mine or explosive. To forecast whether it is rock or mine, logistic regression will be used, which is highly useful for binary data.
The workflow of this project needs to collect solar data the experiment can be done where the solar is used to send and receive signals bounce back from metal signals and some rocks because the mines will be made of metals collect this data which will be obtained from rock and metal.
About Dataset Context Dataset is collection of sonar data. Despite the fact that the dataset is modest, it contains roughly 60 features (attributes). This is an excellent first project because
1.It's a classification problem, therefore you may experiment using a simpler sort of supervised learning method.
2.It is a multi-class classification (multi-nominal) issue that may need some specific treatment.
3.It is tiny and readily fits into memory since it just contains 60 properties and 207 rows.
All of the numerical properties are in the same units and scale, so no extra scaling or transformations are required to get started.
Content It contains various data column which consist sonar data. Last column tells us weather it has found rock or mine. Target Column consist of :
R - > Rock
M -> Mine
this entire End to End small Machine Learning project,
1.Importing useful libraries
2.Collection of Data
3.Data Preprocessing
4.Split the data into Test Data and Train Data
5.Make Trained ML Models
6.Feed Test Data into our Trained ML Models to predict
Thank you !!