原文:https://medium.com/learning-new-stuff/how-to-learn-neural-networks-758b78f2736e#.ly5wpz44d This is the second post in a series of me trying to learn something new over a short period of time. The first time consisted of learning how to do machine…

Neural networks is a model inspired by how the brain works. It is widely used today in many applications: when your phone interprets(解释口译) and understand your voice commands, it is likely that a neural network is helping to understand your speech; wh…

Andrew NG的Machine learning课程地址为:https://www.coursera.org/course/ml 神经网络一直被认为是比较难懂的问题,NG将神经网络部分的课程分为了两个星期来介绍,可见Neural Networks内容之多.言归正传,通过之前的学习我们知道,使用非线性的多项式能够帮助我们建立更好的分类模型.但当遇特征非常多的时候,需要训练的参数太多,使得训练非常复杂,使得逻辑回归有心无力. 例如我们有100个特征,如果用这100个特征来构建一个非线性的多项式模…

1506.01186-Cyclical Learning Rates for Training Neural Networks 论文中提出了一种循环调整学习率来训练模型的方式. 如下图: 通过循环的线性调整学习率,论文作者观察到的一种比较典型的曲线如下图: 图中,使用循环调整方式的模型,虽然训练中准确度有很大的波动,但是这种波动并不影像模型很快的收敛,并且以更快的速度收敛到了固定学习率或者学习率衰减方案中能达到的最高准确率. 这种方式需要设置的超参有三个, min bound,max bound…

The Neural Network is one of the most powerful learning algorithms (when a linear classifier doesn't work, this is what I usually turn to), and this week's videos explain the 'backprogagation' algorithm for training these models. In this week's progr…

Week 3 Quiz - Shallow Neural Networks(第三周测验 - 浅层神经网络) \1. Which of the following are true? (Check all that apply.) Notice that I only list correct options(以下哪一项是正确的?只列出了正确的答案) [ ]…

原文 http://blog.csdn.net/abcjennifer/article/details/7749309 本栏目(Machine learning)包括单参数的线性回归.多参数的线性回归.Octave Tutorial.Logistic Regression.Regularization.神经网络.机器学习系统设计.SVM(Support Vector Machines 支持向量机).聚类.降维.异常检测.大规模机器学习等章节.所有内容均来自Standford公开课machine…

Logistic regression is a method for classifying data into discrete outcomes. For example, we might use logistic regression to classify an email as spam or not spam. In this module, we introduce the notion of classification, the cost function for logi…

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…

这学期一直在跟进 Coursera上的 Machina Learning 公开课, 老师Andrew Ng是coursera的创始人之一,Machine Learning方面的大牛.这门课程对想要了解和初步掌握机器学习的人来说是不二的选择.这门课程涵盖了机器学习的一些基本概念和方法,同时这门课程的编程作业对于掌握这些概念和方法起到了巨大的作用. 课程地址 https://www.coursera.org/learn/machine-learning 笔记主要是简要记录下课程内容,以及MATLAB…