diOSyu的博客

import torch import numpy as np import os import random os.environ['KMP_DUPLICATE_LIB_OK'] = 'True' true_w = [2, -3] true_b = 4 num_inputs = 2 num_examples = 1000 def get_train_data(): features = torch.from_numpy(np.array(np.random.normal(0.0, 1.0.

- **Q1 矩阵运算** 读取matrixA.txt and matrixB.txt 进行矩阵乘法运算 由小到大排序后输出 numpy matrixA.txt 8,4,2,3,5,4,4,2,6,6,7,1,3,3,5,6,8,3,9,4,9,9,2,5,3,2,6,6,5,2,6,7,7,5,9,3,5,8,8,9,5,7,7,8,1,6,3,8,4,3 matrixB.txt 7,3,2,9,9,2,.

1. 人工智能、机器学习、深度学习之间的关系 2. 人工智能：将通常由人类完成的智力任务自动化。 3. 机器学习