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进阶高级测试工程师

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全部文章（共158篇）

题解 | 损失函数

import numpy as np def calculate_loss(real_values, predicted_values, delta): mse = np.mean((real_values - predicted_values) ** 2) mae = np.m...

2025-03-04

0 74

题解 | 异常值与缺失值

import numpy as np def preprocess_data(): n=(int)(input()) li=[] for i in range(n): num=float(input()) li.append(num) ...

2025-03-04

0 102

题解 | 特征扩展实现

import numpy as np def feature_scaling(data): # 补全代码 # 标准化 (Z-score 标准化) mean = np.mean(data, axis=0) std = np.std(data, axis=0) ...

2025-03-04

0 86

题解 | 使用梯度下降的线性回归

import numpy as np def linear_regression_gradient_descent(X, y, alpha, iterations): # 补全代码 m, n = X.shape theta = np.zeros((n,1)) # 包括截距项...

2025-03-04

0 106

题解 | 实现压缩行稀疏矩阵（CSR）格式转换

import numpy as np import scipy.sparse def compressed_row_sparse_matrix(dense_matrix): csr_matrix = scipy.sparse.csr_matrix(dense_matrix) vals...

2025-03-03

0 76

题解 | 将向量转换为对角矩阵

import numpy as np def make_diagonal(x): arr = np.array( x , dtype=np.float32 ) return np.diag(arr) if __name__ == "__main__&q...

2025-03-03

0 90

题解 | 基向量变换矩阵

import numpy as np def transform_basis(B, C): res = np.linalg.solve(C,B).tolist() return res if __name__ == "__main__": B = ...

2025-03-03

0 75

题解 | 基向量变换矩阵

import numpy as np def transform_basis(B, C): res = np.linalg.solve(C,B).tolist() return res if __name__ == "__main__": B = ...

2025-03-03

0 88

题解 | 基向量变换矩阵

import numpy as np def transform_basis(B, C): B1 = np.linalg.inv(B) res = np.linalg.solve(C,B).tolist() return res if __name__ == &quo...

2025-03-03

0 98

题解 | 点积计算器

import numpy as np def calculate_dot_product(vec1, vec2): """ Calculate the dot product of two vectors. Args: vec1...

2025-03-03

0 89