Implementing Recurrent Neural Network from Scratch
Reading CSV file... Parsed 79171 sentences. Found 65376 unique words tokens. Using vocabulary size 8000. The least frequent word in our vocabulary is 'documentary' and appeared 10 times. Example sentence: 'SENTENCE_START i joined a new league this year and they have different scoring rules than i'm used to. SENTENCE_END' Example sentence after Pre-processing: '['SENTENCE_START', 'i', 'joined', 'a', 'new', 'league', 'this', 'year', 'and', 'they', 'have', 'different', 'scoring', 'rules', 'than', 'i', "'m", 'used', 'to', '.', 'SENTENCE_END']' X_train shape: (78483,) y_train shape: (78483,) x: SENTENCE_START what are n't you understanding about this ? ! [0, 51, 27, 16, 10, 858, 54, 25, 34, 69] y: what are n't you understanding about this ? ! SENTENCE_END [51, 27, 16, 10, 858, 54, 25, 34, 69, 1] 2020-02-17 21:40:17: Loss after num_examples_seen=0 epoch=0: 8.987458 2020-02-17 21:42:08: Loss after num_examples_seen=100 epoch=1: 8.973082 2020-02-17 21:44:01: Loss after num_examples_seen=200 epoch=2: 8.951076 2020-02-17 21:45:51: Loss after num_examples_seen=300 epoch=3: 8.907623 2020-02-17 21:47:41: Loss after num_examples_seen=400 epoch=4: 8.803412 2020-02-17 21:49:35: Loss after num_examples_seen=500 epoch=5: 6.866650 2020-02-17 21:51:26: Loss after num_examples_seen=600 epoch=6: 6.271906 2020-02-17 21:53:18: Loss after num_examples_seen=700 epoch=7: 5.981103 2020-02-17 21:55:09: Loss after num_examples_seen=800 epoch=8: 5.786999 2020-02-17 21:57:01: Loss after num_examples_seen=900 epoch=9: 5.654783
参考:
https://github.com/pangolulu/rnn-from-scratch
https://blog.csdn.net/xfwdxt/article/details/102823159
Implementing Recurrent Neural Network from Scratch的更多相关文章
- 从0开始用python实现神经网络 IMPLEMENTING A NEURAL NETWORK FROM SCRATCH IN PYTHON – AN INTRODUCTION
code地址:https://github.com/dennybritz/nn-from-scratch 文章地址:http://www.wildml.com/2015/09/implementing ...
- 计算机视觉学习记录 - Implementing a Neural Network from Scratch - An Introduction
0 - 学习目标 我们将实现一个简单的3层神经网络,我们不会仔细推到所需要的数学公式,但我们会给出我们这样做的直观解释.注意,此次代码并不能达到非常好的效果,可以自己进一步调整或者完成课后练习来进行改 ...
- Recurrent Neural Network系列1--RNN(循环神经网络)概述
作者:zhbzz2007 出处:http://www.cnblogs.com/zhbzz2007 欢迎转载,也请保留这段声明.谢谢! 本文翻译自 RECURRENT NEURAL NETWORKS T ...
- 课程五(Sequence Models),第一 周(Recurrent Neural Networks) —— 1.Programming assignments:Building a recurrent neural network - step by step
Building your Recurrent Neural Network - Step by Step Welcome to Course 5's first assignment! In thi ...
- Sequence Models Week 1 Building a recurrent neural network - step by step
Building your Recurrent Neural Network - Step by Step Welcome to Course 5's first assignment! In thi ...
- Recurrent Neural Network系列2--利用Python,Theano实现RNN
作者:zhbzz2007 出处:http://www.cnblogs.com/zhbzz2007 欢迎转载,也请保留这段声明.谢谢! 本文翻译自 RECURRENT NEURAL NETWORKS T ...
- Recurrent Neural Network系列4--利用Python,Theano实现GRU或LSTM
yi作者:zhbzz2007 出处:http://www.cnblogs.com/zhbzz2007 欢迎转载,也请保留这段声明.谢谢! 本文翻译自 RECURRENT NEURAL NETWORK ...
- Recurrent Neural Network(循环神经网络)
Reference: Alex Graves的[Supervised Sequence Labelling with RecurrentNeural Networks] Alex是RNN最著名变种 ...
- Recurrent Neural Network系列3--理解RNN的BPTT算法和梯度消失
作者:zhbzz2007 出处:http://www.cnblogs.com/zhbzz2007 欢迎转载,也请保留这段声明.谢谢! 这是RNN教程的第三部分. 在前面的教程中,我们从头实现了一个循环 ...
随机推荐
- JavaScript——BOM和DOM
什么是BOM bom:浏览器对象模型 什么是DOM dom:文档对象模型 BOM操作: 调用windows浏览器窗口 windows对象可以通过点调用子对象 windows.navigator对象,可 ...
- blur()低通滤波
blur()函数可以用标准化的盒式过滤器来平滑图像. C++ API: 相关官网资料: https://docs.opencv.org/3.4.1/d4/d86/group__imgproc__fil ...
- 【sql】sql必知必会_02
chapter10 - 常用的sql标准有哪些,在SQL92中是如何使用连接的? sql两个主要的标准sql92.sql95: sql92中的五种连接方式: a.笛卡尔积:是一个数学运算,两个集合X和 ...
- 1.EntityManaget的persist和merge方法的区别
1.persist和merge的区别: Persist:添加 Merge : 分两种情况,当对象存在id,则修改:当对象不存在id则添加. 看个例子: 1 public class Account { ...
- Python | 面向对象中的名词总结
一.变量名称 (最前的序号表示将来用到的频繁程度) 5 全局变量: 1. 文件中出现的变量,不归属于函数及类:2.在函数用用global声明的变量 2 局部变量: 1.类的方法中没有self.,只能在 ...
- (c#)奇数值单元格的数量
题目 解
- php抛出异常Exception和\Exception使用区别
没有定义命名空间的情况下 , Exception和\Exception 均可正常执行抛出异常;定义命名空间的情况 , Exception 会在定义的命名空间下找对应的异常类 , 如果没有定义异常类 , ...
- 十大常见web漏洞及防范
十大常见web漏洞 一.SQL注入漏洞 SQL注入攻击(SQL Injection),简称注入攻击.SQL注入,被广泛用于非法获取网站控制权,是发生在应用程序的数据库层上的安全漏洞.在设计程序,忽略了 ...
- RMQ入门解析
参照大佬博客:https://www.cnblogs.com/yoke/p/6949838.html RMQ(Range Minimum/Maximum Query), 是一种问题,即 查询给定区间 ...
- HBase 启动后HMaster进程自动消失
原因分析 1.hadoop 与 hbase 版本不兼容,导致的异常. 2.log日志信息显示 org.apache.hadoop.hbase.TableExistsException: hbase:n ...