llacr的博客

原创 二类LDA原理公式推导

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原创 2021-10-26

机器学习。。。

原创 2021-10-21

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)device = paddle.get_device()env = gym.make(

原创 2021-09-29

from collections import defaultdictstates = ("Rainy", "Sunny")observations = ("Walk", "Shop", "Clean")start_probability = {"Rainy": 0.6, "Sunny": 0.4}transition_probability = { "Rainy": {"Rainy": 0.7, "Sunny": 0.3}, "Sunny": {"Rainy": 0.4, "Su

原创 2021-09-24

import numpy as npimport matplotlib.pyplot as pltx=np.zeros(100)y=np.zeros(100)x[0]=0y[0]=1y_yuan=np.zeros(100)y_yuan[0]=1for i in range(1,100): k_yuan=(y[i-1]-2*x[i-1]/y[i-1]) y[i]=y[i-1]+0.1*k_yuan x[i] = 0.1 +x[i-1] k_xian = (y[

原创 于成龙1908070231物联192

原创 2021-09-10

import numpy as npdef andActivator(x): if x > 0: return 1 else: return 0class ganzhiji(object): def __init__(self, x): self.x = x self.w = np.random.rand(2, 1) self.b = np.random.rand(1, 1) d

原创 算法的运用

原创 numpy中有哪些简单且实用的操作

入门numpy拉平操作 ravel()和faltten()及reshape(1,-1)的区别联系import numpy as npx = np.array([[1,2,3],[4,5,6],[1,2,3]])x.flatten()array([1, 2, 3, 4, 5, 6, 1, 2, 3])x.ravel()array([1, 2, 3, 4, 5, 6, 1, 2, 3])x.ravel('F')array([1, 4, 1, 2, 5, 2, 3, 6, 3])x