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在所有依靠Gradient Descent和Backpropagation算法来学习的Neural Network中,普遍都会存在Gradient Vanishing Problem.Backpropagation的运作过程是,根据Cost Function进行反向传播,利用Chain Rule去计算n层之前某一weight上的梯度,从而更新该weight.而事实上,在网络层次较深的情况下,我们获得的weight梯度,随着反向传播层次的深入,会呈现越来越小的状态.从而,在靠近输出端的Layers…
Main Menu Fortune.com       E-mail Tweet Facebook Linkedin Share icons By Roger Parloff Illustration by Justin Metz SEPTEMBER 28, 2016, 5:00 PM EDT WHY DEEP LEARNING IS SUDDENLY CHANGING YOUR LIFE Decades-old discoveries are now electrifying the comp…
Growing Pains for Deep Learning Advances in theory and computer hardware have allowed neural networks to become a core part of online services such as Microsoft's Bing, driving their image-search and speech-recognition systems. The companies offering…
Deep Learning Libraries by Language Tweet         Python Theano is a python library for defining and evaluating mathematical expressions with numerical arrays. It makes it easy to write deep learning algorithms in python. On the top of the Theano man…
一.导论 1.1 人工智能.机器学习.深度学习 人工智能.机器学习 人工智能:1980年代达到高峰的是专家系统,符号AI是之前的,但不能解决模糊.复杂的问题. 机器学习是把数据.答案做输入,规则作输出.而传统的是把数据.规则作输入,答案作输出.和统计学有关,但是比统计学解决问题更加复杂. 机器学习三要素: 输入. 期望的输出. 衡量指标. 机器学习中的「学习」,就是指寻找更好的表达. 深度学习 深度学习(Deep learning)中的深度,是指递进式层级的表达.层数,就是深度.层数一般10层到…
The unstable gradient problem: The fundamental problem here isn't so much the vanishing gradient problem or the exploding gradient problem. It's that the gradient in early layers is the product of terms from all the later layers. When there are many…
声明:所有内容来自coursera,作为个人学习笔记记录在这里. Gradient Checking Welcome to the final assignment for this week! In this assignment you will learn to implement and use gradient checking. You are part of a team working to make mobile payments available globally, and…
Gradient Checking Welcome to this week's third programming assignment! You will be implementing gradient checking to make sure that your backpropagation implementation is correct. By completing this assignment you will: - Implement gradient checking…
在之前的强化学习文章里,我们讲到了经典的MDP模型来描述强化学习,其解法包括value iteration和policy iteration,这类经典解法基于已知的转移概率矩阵P,而在实际应用中,我们很难具体知道转移概率P.伴随着这类问题的产生,Q-Learning通过迭代来更新Q表拟合实际的转移概率矩阵 P,实现了强化学习在大多数实际场景中的应用.但是,在很多情况下,诸多场景下的环境状态比较复杂,有着极大甚至无穷的状态空间,维护这一类问题的Q表使得计算代价变得很高,这时就有了通过Deep网络来…
Deep Learning in a Nutshell: History and Training This series of blog posts aims to provide an intuitive and gentle introduction to deep learning that does not rely heavily on math or theoretical constructs. The first part in this series provided an…