Notes on Training recurrent networks online without backtracking Link: http://arxiv.org/abs/1507.07680 Summary This paper suggests a method (NoBackTrack) for training recurrent neural networks in an online way, i.e. without having to do backprop th
Paper: ImageNet Classification with Deep Convolutional Neual Network Achievements: The model addressed by Alex etl. achieved top-1 and top-5 test error rate of 37.5% and 17.0% of classifying the 1.2 million high-resolution images in the ImageNet LSVR
Adviceforapplyingmachinelearning Deciding what to try next 现在我们已学习了线性回归.逻辑回归.神经网络等机器学习算法,接下来我们要做的是高效地利用这些算法去解决实际问题,尽量不要把时间浪费在没有多大意义的尝试上,Advice for applying machine learning & Machinelearning system design 这两课介绍的就是在设计机器学习系统的时候,我们该怎么做? 假设我们实现了一个正则化的线性回
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/po
Andrew NG的Machine learning课程地址为:https://www.coursera.org/course/ml 在Linear Regression部分出现了一些新的名词,这些名词在后续课程中会频繁出现: Cost Function Linear Regression Gradient Descent Normal Equation Feature Scaling Mean normalization 损失函数 线性回归 梯度下降 正规方程 特征归一化 均值标准化 Mode