m0_61403154的博客

原创 请对我的服务方法二

原创 而二哥如果仍让人阿

原创 2476218

import gym, osfrom itertools import countimport paddleimport paddle.nn as nnimport paddle.optimizer as optimimport paddle.nn.functional as Ffrom paddle.distribution import Categoricalprint(paddle.__version__)2.0.2device = paddle.get_device()e

原创 2476218

import paddlefrom paddle.nn import Linearimport paddle.nn.functional as Fimport osimport numpy as npimport matplotlib.pyplot as plt/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/matplotlib/__init__.py:107: DeprecationWarning: Usi

原创 2476218

import paddleimport paddle.nn.functional as Ffrom paddle.vision.transforms import ToTensorimport numpy as npimport matplotlib.pyplot as pltprint(paddle.__version__)transform = ToTensor()cifar10_train = paddle.vision.datasets.Cifar10(mode='train',

原创 Untitled20

import numpy as npimport mathfrom numpy import matrix as matfrom sympy import *"""这回是真的一点没看懂，搜了个函数就用了文件要求的线代水平超过我现有水平了，手算完全不会"""'\n这回是真的一点没看懂，搜了个函数就用了\n\n文件要求的线代水平超过我现有水平了，手算完全不会\n\n'X0 = (2.5+0.5+2.2+1.9+3.1+2.3+2.0+1.0+1.5+1.1) / 10Y0 = 1

原创 Viterbi

import numpy as np#条件粘上，根据理论推导的结果,晴雨雨的概率最高states = ('Rainy', 'Sunny')observations = ('walk', 'shop', 'clean')start_probability = {'Rainy': 0.6, 'Sunny': 0.4}transition_probability = { 'Rainy' : {'Rainy': 0.7, 'Sunny': 0.3}, 'Sunny' : {'Rai

原创 2021-09-29

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原创 Untitled13

'''改进欧拉算法'''import numpy as npimport math#定义函数def f(x,y): return 1.1*y-0.2*x/ydef f1(x,y): return y-2*x/y#构造Eulerdef Euler(x0,y0,t,f,f1): yi=y0 xi=x0 for i in range(1,100): x=xi+t*i yp=yi+t*f(xi,yi) .

原创 Untitled12

'''尝试下写注释的感觉'''import numpy as npimport mathimport random'''#生成随机函数def random_number(a,b): return (b-a)*random.random+a '''#生成矩阵def makwmatrix(m,n,fill =0.0): a =[] for i in range(20): a.append([fill]*n) return a

原创 2021-09-17

原创 2021-09-15

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原创 Perception

import numpy as np''''''class per(object): def __init__(self,input_num,step): self.step = step self.weights = [0.0 for _ in range(input_num)] self.bias = 0.0 '''''' def train(self,input_vec

原创 costFunction

import numpy as npimport matplotlibimport mathx1 = np.array([[2104,3],[1600,3],[2400,3],[1416,2]])x2 = np.array([3,3,3,2])t = np.array([400,330,369,232])alpha = 0.01th0 = np.random.random()th1 = np.random.random()th2 = np.random.random()

原创 Numpy

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