prev_layer.output_dropout, self.mini_batch_size) self.output = self.layers[-1].output self.output_dropout = self.layers[-1].output_dropout def SGD(self, training_data, epochs, mini_batch_size, eta, validation_data, test_data, lmbda=0.0): """Train the network using mini-batch...
Neural networks approach the problem in a different way. The idea is to take a large number of handwritten digits, known as training examples, and then develop a system which can learn from those training examples. In other words, the neural network uses the examples to automatically infer rul...
原作名:Michael Nielsen 出版年:2016-1 页数:224 装帧:online ISBN:9780780354197 豆瓣评分 9.5 249人评价 5星 83.1% 4星 14.5% 3星 2.4% 2星 0.0% 1星 0.0% 评价: 写笔记 写书评 加入购书单 分享到 推荐 内容简介· ··· http://neuralnetworksanddeeplearning.com/ 目录·...
增加基于 momentum 的随机梯度下降到 network2.py 中。 证明公式 (111) 1. 这个µ类似于物理中的摩擦力,这里用来约束v的变化,µ=1时,没有摩擦,速度由▽C决定,速度每次都在叠加,梯度下降的速度将比正常的梯度下降速度快很多;µ=0时,存在很大的摩擦,速度无法叠加,这个时候就等同于通常所说的梯度下降。在...
network correctly classifies the digit. To see how learning might work, suppose we make a small change in some weight (or bias) in the network. What we'd like is for this small change in weight to cause only a small corresponding change in the output from the network. As we'll see ...
最近开始看Michael Nilson的Neural Network and Deep Learning,这位老兄最初是做量子物理研究的,后来转向了科普工作,写了很多科学普及读物,有兴趣的童鞋可以关注他的主页:http://michaelnielsen.org/。就这本书的话,看了几段之后感觉讲得还不错,深入浅出,每次有一些疑惑的地方发现后面都跟了解释,于是决定认真地读一...
《Neural Network and Deep Learning》_chapter4: A visual proof that neural nets can compute any function文章总结(前三章翻译在百度云里) 链接:http://neuralnetworksanddeeplearning.com/chap4.html; Michael Nielsen的《Neural Network and Deep Learning》教程中的第四章主要是证明神经网络可以用来表示任何一...
network2.py 的接口和 network.py 稍微不同,但是过程还是很清楚的。你可以使用如 help(network2.Network.SGD) 这样的命令来检查对应的文档。 import mnist_loader training_data, validation_data, test_data \ ... mnist_loader.load_data_wrapper() import network2 net network2.Network([784, 30, 10], ...
Michael Nielsen is a scientist, writer, and programmer. He works on ideas and tools that help people think and create, both individually and collectively. Reviews, Ratings, and Recommendations: Amazon Amazon (Make Your Own Neural Network)Related...