# Code samples for "Neural Networks and Deep Learning" (Python 3.x version)
This repository contains code samples for my (forthcoming) book on
"Neural Networks and Deep Learning".
As the code is written to accompany the book, I don't intend to add
new features. However, bug reports are welcome, and you should feel
free to fork and modify the code.
## Changes
This is the code for online book "Neural Networks and Deep Learning". But it is modified for Python 3.x.
If you are interested in that book but only prefer to python 3, you can use this version.
My homepage : http://www.liuxiao.org
## License
MIT License
Copyright (c) 2012-2015 Michael Nielsen
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
没有合适的资源?快使用搜索试试~ 我知道了~
"Neural Networks and Deep Learning" by Michael Nielsen 中英文(文字版)
共109个文件
png:48个
py:35个
json:14个
需积分: 25 27 下载量 14 浏览量
2018-04-23
13:47:44
上传
评论
收藏 51.5MB 7Z 举报
温馨提示
深度学习大牛的权威之作。CNN的第一层通常都是卷积层。你必须记住的第一件事应当是卷积层(conv layer)的输入是什么。就像之前说的,输入是一个32*32*3的像素数列。要解释这个卷积层,最好的办法就是想象一下下面场景:你举着手电筒将光束打在一幅图像的左上角。我们假定这个光束覆盖的范围是5*5。
资源推荐
资源详情
资源评论
收起资源包目录
"Neural Networks and Deep Learning" by Michael Nielsen 中英文(文字版) (109个子文件)
Python3 Code.7z 18.03MB
.gitignore 52B
mnist.pkl.gz 16.26MB
neural-networks-and-deep-learning.iml 398B
data_1000.json 5.13MB
norms_during_training_4_layers.json 46KB
norms_during_training_3_layers.json 35KB
norms_during_training_2_layers.json 23KB
overfitting.json 21KB
regularized.json 21KB
multiple_eta.json 2KB
overfitting_full.json 2KB
regularized_full.json 2KB
weight_initialization_30.json 456B
weight_initialization_100.json 456B
initial_gradient.json 272B
more_data.json 63B
more_data_svm.json 63B
README.md 2KB
README.md 257B
Neural Networks and Deep Learning.pdf 13.4MB
Neural Networks and Deep Learning ╓╨╬─░µ.pdf 3.37MB
misleading_gradient.png 186KB
false_minima.png 147KB
valley.png 90KB
valley2.png 83KB
pca_hard_data_fit.png 80KB
regularized2.png 67KB
overfitting2.png 62KB
misleading_gradient_contours.png 58KB
mnist_100_digits.png 57KB
pca_hard_data.png 52KB
training_speed_4_layers.png 50KB
regularized_full.png 49KB
multiple_eta.png 45KB
overfitting_full.png 44KB
training_speed_3_layers.png 43KB
more_data_comparison.png 43KB
training_speed_2_layers.png 42KB
weight_initialization_30.png 41KB
weight_initialization_100.png 40KB
overfitting3.png 38KB
overfitting1.png 36KB
regularized1.png 36KB
more_data_log.png 34KB
more_data.png 32KB
overfitting4.png 30KB
cost_vs_iterations_trapped.png 30KB
backprop_magnitude_nabla.png 29KB
cost_vs_iterations.png 28KB
relu.png 25KB
tanh.png 23KB
sigmoid.png 23KB
mnist_30_component_pca.png 19KB
mnist_30_unit_autoencoder.png 18KB
test.png 18KB
mnist_10_unit_autoencoder.png 18KB
step.png 17KB
mnist_100_unit_autoencoder.png 17KB
mnist_100_30_deep_autoencoder.png 17KB
mnist_really_bad_images.png 12KB
digits.png 8KB
digits_separate.png 8KB
mnist_2_and_1.png 5KB
more_data_rotated_5.png 5KB
mnist_complete_zero.png 5KB
mnist_first_digit.png 5KB
more_data_5.png 5KB
mnist_other_features.png 5KB
mnist_top_left_feature.png 4KB
network2.py 14KB
network3.py 13KB
conv.py 12KB
mnist.py 12KB
overfitting.py 7KB
network.py 6KB
deep_autoencoder.py 4KB
generate_gradient.py 4KB
more_data.py 4KB
gradient_descent_hack.py 3KB
mnist_loader.py 3KB
mnist_autoencoder.py 3KB
common_knowledge.py 3KB
weight_initialization.py 3KB
backprop_magnitude_nabla.py 3KB
perceptron_learning.py 3KB
mnist_average_darkness.py 3KB
expand_mnist.py 2KB
multiple_eta.py 2KB
deep_learning.py 2KB
valley2.py 1KB
mnist_pca.py 1KB
misleading_gradient.py 1KB
valley.py 1KB
serialize_images_to_json.py 1KB
false_minima.py 1KB
pca_limitations.py 782B
mnist_svm.py 730B
misleading_gradient_contours.py 493B
relu.py 416B
共 109 条
- 1
- 2
资源评论
best021
- 粉丝: 0
- 资源: 12
上传资源 快速赚钱
- 我的内容管理 展开
- 我的资源 快来上传第一个资源
- 我的收益 登录查看自己的收益
- 我的积分 登录查看自己的积分
- 我的C币 登录后查看C币余额
- 我的收藏
- 我的下载
- 下载帮助
安全验证
文档复制为VIP权益,开通VIP直接复制
信息提交成功