sample classification add

Makefile

@@ -1,5 +1,10 @@
 install:
 	pip install -r requirements.txt
 
-runhello:
+run1:
 	python hello.py
+run2:
+	python sample_classification.py
+run3:
+	python hello.py
+	python sample_classification.py

README.md

@@ -1,2 +1,2 @@
 # HuFaMLops
-Using Higging Face model to learn MLops
+Using Hugging Face model to learn MLops

requirements.txt

@@ -1,2 +1,3 @@
 pandas
-numpy
+numpy
+scikit-learn

sample_classification.py

@@ -0,0 +1,25 @@
+import numpy as np
+from sklearn.linear_model import LogisticRegression
+
+# Generate random data
+X = np.random.randint(0, 100, (1000, 2))
+y = np.random.randint(0, 2, 1000)
+
+# Split the data into training and test sets
+X_train = X[:750]
+y_train = y[:750]
+X_test = X[750:]
+y_test = y[750:]
+
+# Create the classifier
+clf = LogisticRegression()
+
+# Train the classifier
+clf.fit(X_train, y_train)
+
+# Predict the labels of the test set
+y_pred = clf.predict(X_test)
+
+# Evaluate the accuracy of the classifier
+accuracy = np.mean(y_pred == y_test)
+print("Accuracy:", accuracy)