matlab machine learning toolbox

if you have a machine learning problem this problem has multiple special If you can ensure that these features are in a similar range, I mean to make sure that the values of the different features are within a similar range the gradient descent method can converge faster specifically if you have a problem with two features where X1 is the size of the house area Its value is between 0 and 2000 X2 is the n

This semester has been to follow up on the Coursera Machina learning public class, the teacher Andrew Ng is one of the founders of Coursera, machine learning aspects of Daniel. This course is a choice for those who want to understand and master machine learning. This course

~ ~): Machine learning, data mining (the second half of the main entry): "Introduction to Data Mining" read a few chapters, feel good. Read the review again. "Machine learning" Stanford Open Class is the main. "Linear Algebra", seventh edition, American Steven J.leon There are examples of applications, looking at

achievements of neuroscientists on visual nerve mechanism, which has a reliable biological basis.Second, convolutional neural networks can automatically learn the corresponding features directly from the original input data, eliminating the feature design process required by the General machine learning algorithm, saving a lot of time, and learning and discoveri

In Coursera Stanford Machine Learning,lecturer strongly recommended open source programming environment octave Start, so I also downloaded to try itReference Link: http://www.linuxdiyf.com/linux/22034.html******************************************************************************Installation (Ubuntu16.04): I saw the Xia Guan Web, Ubuntu has been updated to 4.0.3, but still choose stable, this should be 4

Hello everyone, I am mac Jiang, today and everyone to share the coursera-ntu-machine learning Cornerstone (Machines learning foundations)-Job three q6-10 C + + implementation. Although there are many great gods in many blogs have given the implementation of Phython, but given the C + + implementation of the article is significantly less, here for everyone to prov

Original address: http://blog.csdn.net/abcjennifer/article/details/7716281This column (machine learning) includes linear regression with single parameters, linear regression with multiple parameters, Octave Tutorial, Logistic Regression, regularization, neural network, design of the computer learning system, SVM (Support vector machines), clustering, dimensionali

PrefaceTonight I took a bean leaf in the knowledge of the hosted Live: machine learning with my academic routine.The purpose of my participation is that I want to know how the machine learning has a certain effect of peers, how to do the academic, how to learn the subject.Take part in this Live, come back to the conclu

Starter Book List The beauty of mathematics PDFThe author Wu Everyone is familiar with it. The application of mathematics in the fields of machine learning and natural language processing is described in a very popular language. "Programming Collective Intelligence" ("collective Wisdom Programming") PDFAuthor Toby Segaran is also the author of Beautifuldata:the Stories Behind Elegant Data Solutions (t

widely used in this book. The Python development environment also provides an interactive shell environment that allows users to view and detect program content during program development. In the future, the python development environment will integrate the pylab module, which combines numpy, scipy, and matplotlib into a development environment. When writing this book, pylab has not yet been integrated into the python environment, but we will certainly find it in the python development environm

Starter Book List The beauty of mathematics PDFThe author Wu Everyone is familiar with it. The application of mathematics in the fields of machine learning and natural language processing is described in a very popular language. "Programming Collective Intelligence" ("collective Wisdom Programming") PDFAuthor Toby Segaran is also the author of Beautifuldata:the Stories Behind Elegant Data Solutions (t

Python is widely used in scientific computing: computer vision, artificial intelligence, mathematics, astronomy, and so on. It also applies to machine learning and is expected. This article lists and describes the most useful machine learning tools and libraries for Python. In this list, we do not require these librar

This paper mainly records the cost function of neural network, the usage of gradient descent in neural network, the reverse propagation, the gradient test, the stochastic initialization and other theories, and attaches the MATLAB code and comments of the relevant parts of the course work. Concepts of neural networks, models, and calculation of predictive classification using forward propagation refer to Andrew Ng

');Sortdisclass = Sortdis';%%Findclass= Sort (2:1: k); member= Unique (class); Num=size (member); Max=0; fori = 1: num Count= Find (class==member (i)); ifCount >Max Max=count; Label=member (i); Endenddisp ('The final classification results are:'); fprintf ('%d\n', label)After running the result is that the final classification result is: 2. The same as the expected result.In a word, with Matlab time relatively long point, naturally also handy point, b

this regard, the first Scikit-learn python system, ease of use not to say, the document is also moving to No. Alternative to spark in the Mllib and Mahout, the pros and cons do not repeat, a check will be clear. If it is a statistically cheese, using R or MATLAB is of course also very good.4. MathematicalStatistics/probability/optimization (convex optimization), in which all the knowledge deep like the sea, and really short. But the human energy is l

Write in front of the crap:Well, I have to say Fish C markdown Text editor is very good, full-featured. Again thanks to the little turtle Brother's python video Let me last year in the next semester of the introduction of programming, fell in love with the programming of the language, because it is biased statistics, after the internship decided to put the direction of data mining, more and more found the importance of specialized courses. In the days when everyone was busy attending various tra

regression as shown below, (note that in matlab the vector subscript starts at 1, so the theta0 should be theta (1)).MATLAB implementation of the logistic regression the function code is as follows:function[J, Grad] =Costfunctionreg (Theta, X, y, Lambda)%costfunctionreg Compute Cost andgradient for logistic regression with regularization% J=Costfunctionreg (Theta, X, y, Lambda) computes the cost of using%

components are 0.5 and 1 respectively) X = [0 0; 1 0; 0 2] D = Pdist (X, ' Seuclidean ', [0.5,1]) Results: D = 2.0000 2.0000 2.8284 6. Markov distance (Mahalanobis Distance) (1) Markov distance definition There are m sample vectors x1~xm, the covariance matrix is denoted as s, the mean values are denoted as vector μ, and the Markov distances of sample vectors x to u are expressed as: Where the Markov distance between the Vector XI and XJ is defined as: If the covariance matrix is a unit mat

Http://blog.sina.com.cn/s/blog_6b99cdb50101ix0l.htmlOne of the math related to machine learning and computer vision(The following is a space article to be transferred from an MIT bull, which is very practical:)DahuaIt seems that mathematics is not always enough. These days, in order to solve some of the problems in the library, also held a mathematical textbook. From the university to the present, the class

represent the neural network layer, which is very efficient for linear algebra and similar to Numpy arrays. Decaf Decaf is a deep learning library recently released by UC Berkeley. In the challenges of Imagenet classification, it is found that its neural network implementation is very advanced (state of art ). Nolearn If you want to use the excellent Scikit-learn library API in deep learning, encapsulating