概率论复习 概率(Probability) 频率学派(Frequentist):由大量试验得到的期望频率(致命缺陷:有些事情无法大量试验,例如一封邮件是垃圾邮件的概率,雷达探测的物体是一枚导弹的概率): 贝叶斯学派(Bayesian):基于已有信息而对预测结果的不确定性: 离散随机变量(Discrete Random Variables) 设\(X \in \left \{x_{1},\ x_{2},\ ...,\ x_{n} \right \}\) 为离散随机变量 概率质量函数(Probabi…

If user has told us some relevant and some irrelevant documents, then we can proceed to build a probabilistic classifier, such as a Naive Bayes model. Can we use probabilities to quantify our uncertainties? Ranking method:  Rank by probability of rel…

http://blog.csdn.net/pipisorry/article/details/51461878 概率图模型Graphical Models简介 完全通过代数计算来对更加复杂的模型进行建模和求解.然而,我们会发现,使用概率分布的图形表示进行分析很有好处.这种概率分布的图形表示被称为概率图模型( probabilistic graphical models ).这些模型提供了几个有用的性质:• 它们提供了一种简单的方式将概率模型的结构可视化,可以用于设计新的模型.• 通过观察图形,我…

目录 Probabilistic Graphical Models Statistical and Algorithmic Foundations of Deep Learning 01 An overview of DL components Historical remarks: early days of neural networks Reverse-mode automatic differentiation (aka backpropagation) Modern building…

Awesome Courses  Introduction There is a lot of hidden treasure lying within university pages scattered across the internet. This list is an attempt to bring to light those awesome courses which make their high-quality material i.e. assignments, lect…

    转自:https://blog.infermedica.com/three-challenges-youre-going-to-face-when-building-a-chatbot/   Three challenges you're going to face when building a chatbot Adam Radziszewski on Dec. 01, 20166 min read Developing your own chatbot? You're likely…

转自:http://www.asimovinstitute.org/neural-network-zoo/ THE NEURAL NETWORK ZOO POSTED ON SEPTEMBER 14, 2016 BY FJODOR VAN VEEN   With new neural network architectures popping up every now and then, it's hard to keep track of them all. Knowing all the a…

Andrej Karpathy blog About Hacker's guide to Neural Networks A Survival Guide to a PhD Sep 7, 2016 This guide is patterned after my "Doing well in your courses", a post I wrote a long time ago on some of the tips/tricks I've developed during my…

This article come from HEREARS-L1: Learning Tuesday 10:30–12:30; Oral Session; Room: Leonard de Vinci 10:30  ARS-L1.1—GROUP STRUCTURED DIRTY DICTIONARY LEARNING FOR CLASSIFICATION Yuanming Suo, Minh Dao, Trac Tran, Johns Hopkins University, USA; Hojj…

Let $X=\{x_1,x_2,...,x_n\}$ be a finite set and let $P$ be a probability function defined on all subsets of $X$ with $P(\{x_i\})=a_i,~1\leq i \geq n,~0<a_i<1$ for i and $\sum^{n}_{i=1}=1$. $X$ together with $P$ is a discrete (finite) probability dis…