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[Neural Networks] Momentum

一.目的 加快参数的收敛速度. 二.做法 另第t次的权重更新对第t+1次的权重更新造成影响. 从上式可看出,加入momentum后能够保持权重的更新方向,同时加快收敛.通常alpha的取值为[0.7, 0.95]…

Coursera Deep Learning 2 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization - week2, Assignment(Optimization Methods)

声明:所有内容来自coursera,作为个人学习笔记记录在这里. 请不要ctrl+c/ctrl+v作业. Optimization Methods Until now, you've always used Gradient Descent to update the parameters and minimize the cost. In this notebook, you will learn more advanced optimization methods that can spee…

课程二(Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization)，第二周（Optimization algorithms） —— 2.Programming assignments:Optimization

Optimization Welcome to the optimization's programming assignment of the hyper-parameters tuning specialization. There are many different optimization algorithms you could be using to get you to the minimal cost. Similarly, there are many different p…

Deep Learning 16：用自编码器对数据进行降维_读论文“Reducing the Dimensionality of Data with Neural Networks”的笔记

前言 论文“Reducing the Dimensionality of Data with Neural Networks”是深度学习鼻祖hinton于2006年发表于<SCIENCE >的论文,也是这篇论文揭开了深度学习的序幕. 笔记 摘要:高维数据可以通过一个多层神经网络把它编码成一个低维数据,从而重建这个高维数据,其中这个神经网络的中间层神经元数是较少的,可把这个神经网络叫做自动编码网络或自编码器(autoencoder).梯度下降法可用来微调这个自动编码器的权值,但是只有在初始化权值…

循环神经网络(RNN, Recurrent Neural Networks)介绍（转载）

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阅读笔记 The Impact of Imbalanced Training Data for Convolutional Neural Networks [DegreeProject2015] 数据分析型

The Impact of Imbalanced Training Data for Convolutional Neural Networks Paulina Hensman and David Masko 摘要 本论文从实验的角度调研了训练数据的不均衡性对采用CNN解决图像分类问题的性能影响.CIFAR-10数据集包含10个不同类别的60000个图像,用来构建不同类间分布的数据集.例如,一些训练集中包含一个类别的图像数目与其他类别的图像数目比例失衡.用这些训练集分别来训练一个CNN,度量其得…

Training Deep Neural Networks

http://handong1587.github.io/deep_learning/2015/10/09/training-dnn.html  //转载于 Training Deep Neural Networks  Published: 09 Oct 2015  Category: deep_learning Tutorials Popular Training Approaches of DNNs — A Quick Overview https://medium.com/@asjad/p…

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Hacker's guide to Neural Networks Hi there, I'm a CS PhD student at Stanford. I've worked on Deep Learning for a few years as part of my research and among several of my related pet projects is ConvNetJS - a Javascript library for training Neural Net…

提高神经网络的学习方式Improving the way neural networks learn

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 chip, draw and fade the ball, building on and modifying their basic swing. In a…

神经网络指南Hacker's guide to Neural Networks

Hi there, I'm a CS PhD student at Stanford. I've worked on Deep Learning for a few years as part of my research and among several of my related pet projects is ConvNetJS - a Javascript library for training Neural Networks. Javascript allows one to ni…