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Video Learning Website learning duration real-time recording-performance optimization practices, real-time performance optimization I. Application Scenario Description The system provides services for teachers to learn online. The video learning website supports online video learning for teachers. During video
Original: http://blog.csdn.net/abcjennifer/article/details/7834256This 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, dimensionality reduction, anomaly detection, large-scale machine
some time ago on the Internet to see the Coursera Open Classroom Big Machine learning Cornerstone Course, more comprehensive and clear machine learning needs of the basic knowledge, theoretical basis to explain. There are several more important concepts and ideas in foundation, first review, and then open the follow-up techniques to learn and summarize the course.1. VC Dimension (VC dimension, very importan
1. Nearest Neighbor Component analysis (NCA) algorithmAbove content reproduced from: http://blog.csdn.net/chlele0105/article/details/130064432. Metric LearningIn machine learning, the main purpose of dimensionality reduction of high dimensional data is to find a suitable low-dimensional space, in which the learning can be better than the original space performance. Each space corresponds to a distance metri
information table, X indicates that the dimensions of the high dimensional input matrix are the high dimension D times the number of samples N, C=xxt, Z represents the dimension reduction output matrix size low dimension d times N, E=zzt, the linear mapping is Z=WTX, the distance matrix between 22 in the high-dimensional space is a, and the SW,SB is LDA respectively. In-class divergence matrices and inter-class divergence matrices, K indicates that a point in manifold
The previous article mentioned the importance of error analysis and setting error metrics. That is to set a real number to evaluate the learning algorithm and measure its performance. With the evaluation and error metrics of the algorithm, one important thing to note is that using an appropriate error metric can sometimes have a very subtle effect on the learning algorithm. This kind of problem is the probl
Learning notes TF042: TF. Learn, distributed Estimator, deep learning Estimator, tf042estimator TF. Learn, an important module of TensorFlow, various types of deep learning and popular machine learning algorithms. TensorFlow official Scikit Flow project migration, launched by Google employee Illia Polosukhin and Tang Y
Source: http://wanghaitao8118.blog.163.com/blog/static/13986977220153811210319/Google's deep-mind team published a bull X-ray article in Nips in 2013, which blinded many people and unfortunately I was in it. Some time ago collected a lot of information about this, has been lying in the collection, is currently doing some related work (want to have a small partner to communicate).First, related articlesOn the DRL, this aspect of the work should be with the deep
Simple examples are used to understand what machine learning is, and examples are used to understand machine learning. 1. What is machine learning? What is machine learning? Different people may have different understandings about this issue. In my personal opinion, to describe machine
Ajax learning notes sorting, ajax learning notes Ajax: Asynchronous JavaScript and Xml, Asynchronous js scripts and xml, which are often used to implement partial Asynchronous page refresh, which is of great help to improve user experience. xml is advantageous in multiple languages, but Ajax uses Json objects rather than Xml to process data. Ajax history... understanding knowledge Ajax belongs to Web Front-
TweenMax animation library Learning (6) and tweenmax animation library Learning Directory TweenMax animation library Learning (1) TweenMax animation library Learning (2) TweenMax animation library Learning (3) TweenMax animation library
1. Training error: The error of the learner in the training set, also known as "experience Error"2. Generalization error: The error of the learner on the new sampleObviously, our goal is to get a better learner on a new sample, which is a small generalization error.3. Overfitting: The learner learns the training sample too well, leading to a decline in generalization performance (learning too much ...). Let me think of some people bookworm, reading de
Reprinted please indicate Source Address: http://www.cnblogs.com/xbinworld/archive/2013/04/21/3034300.html Pattern Recognition and machine learning (PRML) book learning, Chapter 1.1, introduces polynomial curve fitting) The doctor is almost finished. He will graduate next year and start preparing for graduation this year. He feels that he has done a lot of research on machine
Connect 9. Common models or methods of Deep Learning 9.1 AutoEncoder automatic Encoder One of the simplest ways of Deep Learning is to use the features of artificial neural networks. Artificial Neural Networks (ANN) itself are hierarchical systems. If a neural network is given, let's assume that the output is the same as the input, and then train and adjust its parameters to get the weight in each layer. N
Original writing. For more information, see http://blog.csdn.net/xbinworld,bincolumns. Pattern Recognition and machine learning (PRML) book learning, Chapter 1.1, introduces polynomial curve fitting) The doctor is almost finished. He will graduate next year and start preparing for graduation this year. He feels that he has done a lot of research on machine learning
Http://www.javaeye.com/topic/255 by Robbin It's easy to get started with hibernate, and I don't dare to boast of my skills. When I read the hibernate documentation for the first time, I also felt very difficult, but not because hibernate was difficult to grasp, because the hibernate documentation is a permanent layer design experience and best practices everywhere. The Hibernate documentation is accurate. Most of the content is about the persistence layer design of objects, rather than simpl
Machine Learning 3, machine learning K-Nearest Neighbor Algorithm for machine learning in PythonPreface I recently started to learn machine learning. I found a book about machine learning on the Internet called "machine learning p
Many people always ask this question, so here is a summary document for your reference. The following steps areLinuxSystem, not for wince. Maybe you will notice that there are far more people doing Linux research in embedded systems than those doing wince. Many manufacturers also provide information based on Linux. I have been hard to understand. In fact, the wince interface is much better than the Linux interface, and it is very convenient to use. More importantly, the development of Wince is b
Time: 2014.06.26 Location: Base Bytes --------------------------------------------------------------------------------------I. Training error and test error The purpose of machine learning or statistical learning is to make the learned model better able to predict not only known data but also unknown data. Different learning methods produce different models. When
recommended to go online to see the tutorial, this time directly ask the old staff, or let him help. (Time is tight, if the time is ample, you can try to build the development environment)Second: Familiarize yourself with the IDE. First, try to use the IDE as recommended by the project team, and avoid using other Ides to cause problems when the problem occurs, unanswered. Of course, if there is an expert directly in the development of a text editor (mainly in the interpretation of language or s
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