Tensorflow Welcome to the Tensorflow Tutorial! In this notebook you will learn all the basics of Tensorflow. You will implement useful functions and draw the parallel with what you did using Numpy. You will understand what Tensors and operations are,
Building Convolutional Neural Network using NumPy from Scratch https://www.linkedin.com/pulse/building-convolutional-neural-network-using-numpy-from-ahmed-gad/ 教程 | 如何使用纯NumPy代码从头实现简单的卷积神经网络 机器之心 2018-05-29
Python使用numpy实现BP神经网络 本文完全利用numpy实现一个简单的BP神经网络,由于是做regression而不是classification,因此在这里输出层选取的激励函数就是f(x)=x.BP神经网络的具体原理此处不再介绍. import numpy as np class NeuralNetwork(object): def __init__(self, input_nodes, hidden_nodes, output_nodes, le
题目下载[传送门] 题目简述:识别图片中的数字,训练该模型,求参数θ. 出现了一个问题:虽然训练的模型能够有很好的预测准确率,但是使用minimize函数时候始终无法成功,无论设计的迭代次数有多大,如下图: import numpy as np import scipy.io as scio import matplotlib.pyplot as plt import scipy.optimize as op # X:5000*400 # Y:5000*10 # a1:5000*401(后500
题目太长了!下载地址[传送门] 第1题 简述:识别图片上的数字. import numpy as np import scipy.io as scio import matplotlib.pyplot as plt import scipy.optimize as op #显示图片数据 def displayData(X): m = np.size(X, 0) #X的行数,即样本数量 n = np.size(X, 1) #X的列数,即单个样本大小 example_width = int(np.r
import numpy as np import sys def conv_(img, conv_filter): filter_size = conv_filter.shape[1] result = np.zeros((img.shape)) # 循环遍历图像以应用卷积运算 for r in np.uint16(np.arange(filter_size/2.0, img.shape[0]-filter_size/2.0+1)): for c in np.uint16(np.arange(