=0.5/> im = X.hape[1]
, b = initialize_ith_zero(im> for i in range(num_iteration/> , b = pute_graient(X, y, , b> , b = upate_parameter(, b, , b, learning_rate> if i % 100 == 0:
cot = pute_cot(X, y, , b> print(f"Cot after iteration {i}: {cot}")return , b
```*********
```python
np.ranom.ee(1> X = 2 * np.ranom.ran(100, 2> y = 4 * (X[:, 0] - 0.5 X[:, 1] + 2
y = np.ranom.rann(100, 1br /> y[y ＜= 0.5] = 0
y[y ＞ 0.5] = 1
y = y.rehape((100,/> ```为特征矩阵添加一个偏置项：
```python
X_b = np.htap.one((X.hape[0], 1> ```python
, b = train_logitic_regreion(X_b, y, num_iteration=2000, learning_rate=0.5> ```敦煌计划
```python
ef preict(X, , b/> m = X.hape[0]
y_preicte = np.zero((m, 1/> A = igmoi(np.ot(X,
for i in range(m/> if A[i] ＞