All the my learnings and information regarding ML and small practise projects are pushed in this repo !

1. main :

Diabetes Dataset on ML ( Practise )

2. main2 :

Diabetes Dataset on ML ( Practise )

3. classifier1 :

Originally used as an example data set on which Fisher's linear discriminant analysis was applied, it became a typical test case for many statistical classification techniques in machine learning such as support vector machines

Here I have used the iris flower dataset or Fisher's Iris data set to predict the flower species by its different labels like (1) sepal length, (2) sepal width, (3) petal length, (4) petal width and (5) species

from sklearn.datasets import load_iris

iris = load_iris()
iris

This code gives:

{'data': array([[5.1, 3.5, 1.4, 0.2],
                [4.9, 3. , 1.4, 0.2],
                [4.7, 3.2, 1.3, 0.2],
                [4.6, 3.1, 1.5, 0.2],...
'target': array([0, 0, 0, ... 1, 1, 1, ... 2, 2, 2, ...
'target_names': array(['setosa', 'versicolor', 'virginica'], dtype='<U10'), 
...}

3. logistic_regression :