python
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier
iris = datasets.load_iris()
X = iris.data
y = iris.target
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
clf = DecisionTreeClassifier()
clf.fit(X_train, y_train)
y_pred = clf.predict(X_test)
python
import nltk
text = "This is a sample sentence."
tokens = nltk.word_tokenize(text)
tagged = nltk.pos_tag(tokens)
entities = nltk.chunk.ne_chunk(tagged)
python
import cv2
image = cv2.imread('image.jpg')
resized = cv2.resize(image, (320, 240))
blurred = cv2.GaussianBlur(resized, (5, 5), 0)
