AttributeError: module 'numpy' has no attribute 'matrix' while using LogisticRegression.fit

I am new to all this. Likely may have configuration problem.

import pandas as  pd

import matplotlib
import matplotlib.pyplot as plt 
import numpy  as np
%matplotlib inline 
from sklearn.model_selection import train_test_split

from sklearn.metrics import classification_report, accuracy_score
from sklearn.metrics import confusion_matrix
from sklearn.linear_model import LogisticRegression
from sklearn import metrics
import seaborn as sns 

from numpy import matrix
logisticreg = LogisticRegression()
logisticreg.fit(xtrain, ytrain)

Returns

File ...\Python\Python312\Lib\site-packages\sklearn\linear_model\_logistic.py:1303, in LogisticRegression.fit(self, X, y, sample_weight)
   1300 else:
   1301     n_threads = 1
-> 1303 fold_coefs_ = Parallel(n_jobs=self.n_jobs, verbose=self.verbose, prefer=prefer)(
   1304     path_func(
   1305         X,
   1306         y,
   1307         pos_class=class_,
   1308         Cs=[C_],
...
-> 1871     if isinstance(a, np.matrix):
   1872         return asarray(a).ravel(order=order)
   1873     else:


AttributeError: module 'numpy' has no attribute 'matrix'

Running numpy version 1.26.2

Tried running example

import numpy as np
from sklearn.linear_model import LinearRegression
X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
# y = 1 * x_0 + 2 * x_1 + 3`
y = np.dot(X, np.array([1, 2])) + 3
reg = LinearRegression().fit(X, y)
reg.score(X, y)
reg.coef_
reg.intercept_
reg.predict(np.array([[3, 5]]`))

Same error