coursera pgm

To read the. pgm file in C, please link the blog http://blog.csdn.net/a350203223/article/details/13102513 PGM file Format PGM----Portable Graymap format. The PGM format is the minimum standard for grayscale file formats. The format of the PGM file is defined as follows: A

Python detailed process of crawling Coursera course resources, coursera Course Resources Sometimes we need to add some classic things to our favorites and review them from time to time. Some courses on Coursera are undoubtedly classic. Most of Coursera's finishing courses provide complete teaching resources, including ppt, video, and subtitles. It is very easy to

Label: PPM PGM PBM Portable pixmap is a set of portable image formats defined by the netpbm project. These images are in the same format. It is easier to process and has nothing to do with the platform. Therefore, portable is a relatively direct image format. For example, PPM stores the RGB values of each vertex separately. . Therefore, files in the PPM format are not compressed and relatively large. However, because the image format is simple, they a

http://blog.csdn.net/pipisorry/article/details/52489321Markov NetworkMarkov networks are commonly referred to as Markov random fields (Markov random field, MRF) in computer vision.Markov network is a method to characterize the joint distribution on X.Like Bayesian networks, a Markov network can be seen as defining a series of independent assumptions determined by the graph structure.Phi BlogAn example of a misunderstanding of a non-graphic modelP-mapAn example of a Bayesian network that cannot b

http://blog.csdn.net/pipisorry/article/details/52469064the use of independent natureConditional parameterization and conditional independence assumptions are combined to produce a very compact representation of the high-dimensional probability distributions.Independence of random variables[PGM: The basic knowledge of probability theory : The use of independent nature]Conditional Parameterization MethodNote:p (I), p (S | i0), p (S | i1) are all two-ite

I. PGM Figure from: http://blog.sina.com.cn/s/blog_5980285201011z75.html Ii. Reasoning Based on the probability graph model. Example: For example, if a message is sent through a noisy channel, the information is composed of 0 and 1. Due to the noisy, each bit has a probability of 20% error. Due to the characteristics of the sent signal, the probability of 1 followed by 1 and 0 followed by a 0 is 0.9. If a bit string "1101" is received, what is the m

The probabilistic graphical model series is explained by Daphne Koller In the probabilistic graphical model of the Stanford open course. Https://class.coursera.org/pgm-2012-002/class/index) Main contents include (reprinted please indicate the original source http://blog.csdn.net/yangliuy) 1. probabilistic Graph Model Representation and deformation of Bayesian Networks and Markov networks. 2. Reasoning and inference methods, including Exact Inference (

really simple, it can only be used in the case of weak correlation of random variables, but very many cases are actually very weak ... So the naïve Bayes effect surprisingly effectiveNaive Bayes is widely used in various fields. It's not going to unfold here. There are quite a few advantages. Welcome to the discussion and follow the this blog Weibo personal homepage Reprint Please respect the author's labor. Full retention of the above text and links to the article, thank you for

following is a visual sense of conditional independence , 9Figure 9There are 2 coins, one just evenly. There is also an uneven and 90% probability of being able to face up. Of course, the two coins look exactly the same.Now let you take out one. Ready to throw 2 times.You throw it first, you find the face up, and you can believe it. The second or front-facing probability is definitely added. The result of the second coin was affected by the first coin cast.And now I'm telling you, in fact, you

convert a directed graph to an undirected graph, we can simply connect any two nodes to form a fully connected undirected graph. However, we discard all the conditional independence features. However, the moralization process can retain the maximum number of independent features in an undirected graph by adding the least number of connections .) The undirected graph corresponding to the figure above is as follows: Summary: The general step of converting a directed graph to an undirected graph i

The probabilistic graphical model series is explained by Daphne Koller In the probabilistic graphical model of the Stanford open course. Https://class.coursera.org/pgm-2012-002/class/index) Main contents include (reprinted please indicate the original source http://blog.csdn.net/yangliuy) 1. probabilistic Graph Model Representation and deformation of Bayesian Networks and Markov networks. 2. Reasoning and inference methods, including Exact Inference (

used to define probability distribution in a high-dimensional space. Factors can be multiplied (fig. 5), marginalized (fig. 6), and reduced (fig. 7 ). Figure 5 Figure 6 Figure 7 The conditional probability distribution of the student model mentioned above can be drawn in a picture. Each node represents a factor, and some CPDs have become non-conditional probabilities. Figure 8 Chain rule) 9. Probability Distribution is defined by the product of a fact

: "like a stack of the same Board (And the reason for calling it a plate is because the intuition ofthis is a stack of identical plates, that's kind of where the idea comes from, fora plate model.)" The Board draws a small box around the output variable and writes the index of the output variable in the lower right corner of the box. For example, the duplicate score model is indexed by student s: Nested Plates) Nested panels think that the inner layer must be indexed by the outer layer. Ove

Tags: database matlab%{converts The PGM format of the ORL face database to the JPG format %} CLC; % clear all; For i=1:40 for j=1:10 image=imread (strcat (' E:\pic\att_faces\s ',... Int2str (i), ' \ ', Int2str (j), '. PGM '); Imwrite (Image,strcat (' E:\pic\att_faces\s ',... Int2str (i), ' \ ', Int2str (j), '. jpg '); End disp (strcat (' s ', int2str (i), ' end of conversion. ')); End disp (' bulk

The full name of PGM is called the probability map model, and it doesn't feel good until you learn it. Now that I have studied, I feel that it is of great use. Below on some of my Learning and learning journey record down, will inevitably have some wrong ideas, welcome to pass by friends to correct. 2016.12.23I am learning prml This classic textbook, now in the study of 8.4.4 Festival, "and-Product algorithm", a few days to write the sentiment of thi

In Wednesday, we received mass mailings from the Coursera platform, to the effect that Coursera will completely close the Old Course platform on June 30, upgrade to the new course platform, some Old Course resources (course videos, course materials) will not be saved, if you have previously studied the relevant courses, or have the desired courses , Coursera reco

friends, but also hope to get the high people of God's criticism!　　 　　 　　Preface　　[Machine Learning] The Coursera Note series was compiled with notes from the course I studied at the Coursera learning (Andrew ng teacher). The content covers linear regression, logistic regression, Softmax regression, SVM, neural networks, and CNN, among other things, and the main learning materials are from the machine lear

! I've been on this course 3 years ago, and it's been a long time ... Before going to bed to see this question, the day before yesterday wrote an article about learning Python in Coursera, just right question, so excerpt part, hope to be helpful:-) Let's talk about the process of learning Python in Coursera (and recommend this interesting professor, who wants to learn about Python). This is the 0 basic Py

friends leave a message saying they are already charged. Let's go to the official website and check it out! I have taken this course three years ago. It takes a long time ...... I saw this problem before I went to bed. I wrote an article about learning python in coursera the day before yesterday, which is just the right question. So I want to extract some of it and hope it will help me :-) Next, let's talk about how I learned python on

Sometimes we need to put some classic things in the collection, always aftertaste, and Coursera on some of the courses are undoubtedly classic. Most of the end courses in Coursera provide a complete set of teaching resources, including PPT, video and subtitles, which will be very easy to learn when offline. Obviously, we will not go to a file to download a file, Only fools do so, programmers are smart! Wha