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...
原作名:Michael Nielsen 出版年:2016-1 页数:224 装帧:online ISBN:9780780354197 豆瓣评分 9.5 254人评价 5星 82.7% 4星 15.0% 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·...
The main part of the chapter is an introduction to one of the most widely used types of deep network: deep convolutional networks. We'll work through a detailed example - code and all - of using convolutional nets to solve the problem of classifying handwritten digits from the MNIST data se...
Incidentally, when I defined perceptrons I said that a perceptron has just a single output. In the network above the perceptrons look like they have multiple outputs. In fact, they're still single output. The multiple output arrows are merely a useful way of indicating that the output from a...
《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...
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...
Deep Learning, book by Ian Goodfellow, Yoshua Bengio, and Aaron Courville cognitivemedium.com ByMichael Nielsen/ Dec 2019 When a golf player is first learning to play golf, they usually spend most of their time developing a basic swing. Only gradually do they develop other shots, learning to...
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...
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...