• cross entropy loss is not quite the same as optimizing classification accuracy. Althougth the two are correlated.
  • It's not necessarily true that Deep learning approaches are often said to require enormous amount of data to work well. In this competitation, there'are 30,000 examples for 121 classes.
    To achieve this, some tricks are :

    • dropout
    • weight decay
    • data argumentation
    • pre-training
    • pseudo-labeling
    • parameter sharing
  • The method is implemented based on Theano:
    • Python, Numpy, Theano, cuDNN, PyCUDA, Lasagne
    • scikit-image: pre-processing and data argumentation
    • ghalton: quasi-random number generation
  • Hardware:
    • GTX 980, GTX 680, Tesla K40
  • Pre-processing and data argumentation:
    • Normalization: pre-pixel zero mean unit variance

to be finished

"Classifying plankton with deep neural networks" notes的更多相关文章

  1. Classifying plankton with deep neural networks

    Classifying plankton with deep neural networks The National Data Science Bowl, a data science compet ...

  2. Training Deep Neural Networks

    http://handong1587.github.io/deep_learning/2015/10/09/training-dnn.html  //转载于 Training Deep Neural ...

  3. 课程一(Neural Networks and Deep Learning)，第四周（Deep Neural Networks） —— 3.Programming Assignments: Deep Neural Network - Application

    Deep Neural Network - Application Congratulations! Welcome to the fourth programming exercise of the ...

  4. Training (deep) Neural Networks Part: 1

    Training (deep) Neural Networks Part: 1 Nowadays training deep learning models have become extremely ...

  5. 为什么深度神经网络难以训练Why are deep neural networks hard to train?

    Imagine you're an engineer who has been asked to design a computer from scratch. One day you're work ...

  6. [C4] Andrew Ng - Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

    About this Course This course will teach you the "magic" of getting deep learning to work ...

  7. On Explainability of Deep Neural Networks

    On Explainability of Deep Neural Networks « Learning F# Functional Data Structures and Algorithms is ...

  8. Introduction to Deep Neural Networks

    Introduction to Deep Neural Networks Neural networks are a set of algorithms, modeled loosely after ...

  9. 深度神经网络入门教程Deep Neural Networks: A Getting Started Tutorial

    Deep Neural Networks are the more computationally powerful cousins to regular neural networks. Learn ...

随机推荐

  1. 基于.Net的单点登录(SSO)解决方案

    前些天一位朋友要我帮忙做一单点登录,其实这个概念早已耳熟能详,但实际应用很少,难得最近轻闲,于是决定通过本文来详细描述一个SSO解决方案,希望对大家有所帮助.SSO的解决方案很多,但搜索结果令人大失所 ...

  2. JQ点击高亮显示

    <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/ ...

  3. visual studio 2015 修改类class 文件模板

    第一步:找到模板文件 路径:C:\Program Files (x86)\Microsoft Visual Studio 14.0\Common7\IDE\ItemTemplates\CSharp\C ...

  4. oc内存管理总结（一）

    **内存管理 问题 1.什么是ios内存管理? 就是在对象不再被使用的时候,把它即时的从内存中清除掉 2.为什么要使用内存管理? 1.严格的内存管理,能够是我们的应用程在性能上有很大的提高 2.如果忽 ...

  5. B - A + B Again

    Description There must be many A + B problems in our HDOJ , now a new one is coming.         Give yo ...

  6. [转]C++实现系统服务暂停、停止、启动

    /* 名称:系统服务管理 语言:C++ 介绍:对Windows系统服务的状态获取,服务暂停,开启,停止操作代码 */ void CStartServiceDlg::OnBnClickedButton1 ...

  7. JSON之三：获取JSON文本并解释（以google的天气API为例）

    google提供了天气的api,以广州天气为例,地址为: http://api.openweathermap.org/data/2.5/weather?q=guangzhou 返回的结果为: {   ...

  8. Android上使用OpenglES2.0遇到的一点问题

    按照教程开发OpenglES2.0应用,遇到Logcat报错“Called unimplemented OpenGL ES API” 在论坛和stackoverflow上找到了答案. 1.manife ...

  9. Div+Css（一）必备知识

    我只积累我不知道的 参考链接 http://www.kwstu.com/ArticleView/divcss_201442291125960 http://www.kwstu.com/ArticleV ...

  10. Git学习03 －－远程仓库

    把本地库的内容推送到远程(github), 用git push命令,实际上是把当前分支master推送到远程. 由于远程库是空的,我们第一次推送master分支时,加上了-u参数,Git不但会把本地的 ...