ai with python supervised learningclassification in this we will focus on implementing supervised learning classification the classification technique or model attempts to get some conclusion from observed values in classification problemwe have the categorized output such as "blackor "whiteor "teachingand "non-teachingwhile building the classification modelwe need to have training dataset that contains data points and the corresponding labels for exampleif we want to check whether the image is of car or not for checking thiswe will build training dataset having the two classes related to "carand "no carthen we need to train the model by using the training samples the classification models are mainly used in face recognitionspam identificationetc steps for building classifier in python for building classifier in pythonwe are going to use python and scikit-learn which is tool for machine learning follow these steps to build classifier in pythonstep import scikit-learn this would be very first step for building classifier in python in this stepwe will install python package called scikit-learn which is one of the best machine learning modules in python the following command will help us import the packageimport sklearn step import scikit-learn' dataset in this stepwe can begin working with the dataset for our machine learning model herewe are going to use the breast cancer wisconsin diagnostic database the dataset includes various information about breast cancer tumorsas well as classification labels of malignant or benign the dataset has instancesor dataon tumors and includes information on attributesor featuressuch as the radius of the tumortexturesmoothnessand area with the help of the following commandwe can import the scikitlearn' breast cancer datasetfrom sklearn datasets import load_breast_cancer nowthe following command will load the dataset data load_breast_cancer(following is list of important dictionary keysclassification label names(target_namesthe actual labels(targetthe attribute/feature names(feature_names