machine learning course on coursera

lot of things, such as:1. Collect more data and let us have more spam and non-spam samples2. Message-based routing information develop a complex set of features3. The development of a series of complex features based on the message body information, including the processing of the truncated words4. Develop complex algorithms for detecting deliberate spelling errors (writing watch as W4tch)Among the options above, it is very difficult to decide which item to spend time and effort on, making wise

Because there is a very detailed online blog, so this section will not write their own, write can not write others so good and thorough.jerrylead Support Vector Machine series:Support Vector Machine (i): http://www.cnblogs.com/jerrylead/archive/2011/03/13/1982639.htmlSupport Vector Machine (ii): http://www.cnblogs.com/jerrylead/archive/2011/03/13/1982684.htmlSupp

MIT's algorithm introduction Open class, many years ago saw, has not insisted to see, recently looking for summer internship, interview is basically algorithm, had to take time to brush Leetcode, also through this opportunity hope to see this video, the algorithm of the basic skills to play a solid, this public class is still quite good.Before learning other things, remember a lot of notes, and finally lost, want to look at the time has not been found

Find a good article on the internet, paste it directly, add some supplements and your own understanding, and count as this article. My education in the fundamentals of machine learning has mainly come from Andrew Ng's excellent Coursera course on the topic. one thing that wasn't covered in that

Stanford University's Machine learning course (The instructor is Andrew Ng) is the "Bible" for learning computer learning, and the following is a lecture note.First, what is machine learningMachine

chain Monte Carlo method;L variational method;L Optimization: Most of the above methods use optimization algorithms directly or indirectly.According to the function and form similarity of the algorithm, we can classify the algorithm, for example, tree-based algorithm, neural network based algorithm and so on. Of course, the scope of machine learning is very larg

Hello everyone, I am mac Jiang, today and everyone to share the coursera-ntu-machine learning Cornerstone (Machines learning foundations)-Job four q13-20 MATLAB implementation. The previous code was implemented through C + +, but found that C + + implementation of the code is too cumbersome, the job also to change the

Hello everyone, I am mac Jiang, today and everyone to share the coursera-ntu-machine learning Cornerstone (Machines learning foundations)-Job four q13-20 MATLAB implementation.Once the code is implemented through C + +. However, it is too cumbersome to discover that C + + implements this code. This job also need to cha

This week began the University of C + + learning, the main learning content has a header file, simple input and output, int main () ... return 0 programming basic format. The specific learning program is a small program that outputs the specific typeface of Hello World and adds two integers.The main problem I encountered this week is: in understanding the "can be

to learn the "intrinsic" structure of data from the data set of X. In unsupervised learning, the most practical and representative method is Clustering (cluster). For example we can look for a group of people (yellow people inside), everyone has some data to describe (accent, dietary preferences, ...) And so on, we can get a rough idea of the different clusters (cluster) through these characteristics. The concept of these clu

,m)) return jdef clipAlpha(aj,H,L): if aj > H: aj = H if L > aj: aj = L return ajdef smoSimple(dataMatIn, classLabels, C, toler, maxIter): dataMatrix = mat(dataMatIn); labelMat = mat(classLabels).transpose() b = 0; m,n = shape(dataMatrix) alphas = mat(zeros((m,1))) iter = 0 while (iter The running result is shown in figure 8: (Figure 8) If you are interested in the above code, you can read it. If you use it, we recommend using libsvm. References: [1]