<jupyter_start><jupyter_text>Video Series: Introduction to Machine Learning with Scikit-Learn [5] - The Hello World Data Set for ML from Scikit-Learn_Let's understand how the data sets are presented to scikit-learn machine learning algorithm using the Iris dataset, which is sometimes also called as the Hello World dataset of Machine Learning_  Features and Labels- ___Features: A Set of data representing specific characteristics___- ___Labels : Result of those characteristics____Features along with Labels are used in Supervised Learning Models_ ![](fl.png)  The iris data set and contains 150 rows of 4 __FEATURES__ and a single __LABEL__This dataset differentiates between 3 types of iris flower called ___iris setosa, iris versicolor___ and ___iris virginica___. Here is how the 3 flowers look like  ![](images.png)image from wikipedia : https://en.wikipedia.org/wiki/Iris_flower_data_set These 3 species are identified using 4 features called- __Sepal Length__- __Sepal Width__- __Petal Length__- __Petal Width__<jupyter_code>from sklearn.datasets import load_iris
iris_db = load_iris()
iris_db
iris_db.data
iris_db.target
iris_db.target_names
iris_db.feature_names<jupyter_output><empty_output><jupyter_text><jupyter_code>type(iris_db.data), type(iris_db.target), type(iris_db.target_names), type(iris_db.feature_names)
iris_db.data.size, iris_db.data.ndim, iris_db.data.shape
iris_db.target.size, iris_db.target.ndim, iris_db.target.shape
iris_db.DESCR<jupyter_output><empty_output>
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