Diabetes detection using Multivariate Analysis and Machine learning:

Importing libraries and basic packages:

 

Loading diabetes dataset and printing first five rows:

 
Overall information about the dataset:

 
Statistical description of the dataset:

 
Checking for null values:

 
Correlation and heatmap:

 
Countplot to find number of 1's and 0's in outcome column:
 

Splitting the training and testing dataset:

 
Model fitting using Logistic Regression:

Prediction:

 
Confusion Matrix to test the accuracy:

 
Accuracy score: