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I. BACKGROUND In machine learning, there are 2 great ideas for supervised learning (supervised learning) and unsupervised learning (unsupervised learning) Supervised learning, in layman's terms, is you know the answer to the quest

Machine learning is a comprehensive and applied discipline that can be used to solve problems in various fields such as computer vision/biology/robotics and everyday languages, as a result of research on artificial intelligence, and machine learning is designed to enable computers to have the ability to learn as humans do, because we find that computers have the functions to accomplish, Can not be achieved

Today finally the basic knowledge of OC finished, but these knowledge is the most basic, there are a lot of high-level knowledge, this may need to learn slowly behind to understand. The following is the study of the directory of OC Tutorial, if you find that there is something wrong place, please correct me, younger brother is a freshman, more please OC veteran to spray ~ ~1.---Overview of OC Learning articles2, OC Study---The first program HelloWorld

Enhanced Learning (reinforcement learning and Control) [PDF version] enhanced learning. pdfIn the previous discussion, we always given a sample x and then gave or didn't give the label Y. The samples are then fitted, classified, clustered, or reduced to a dimension. However, for many sequence decisions or control problems, it is difficult to have such a regular s

Enhanced Learning (reinforcement learning and Control) [PDF version] enhanced learning. pdfIn the previous discussion, we always given a sample x and then gave or didn't give the label Y. The samples are then fitted, classified, clustered, or reduced to a dimension. However, for many sequence decisions or control problems, it is difficult to have such a regular s

What are two models? We have come to these two concepts from a few words:1, machine learning is divided into supervised machine learning and unsupervised machine learning;2, supervised machine learning is known as training set data categories to train the classifier, unsupervised machine

TensorFlow integrates and implements a variety of machine learning-based algorithms that can be called directly.Supervised learning1) Decision Trees (decision tree)Decision tree is a tree structure, providing people with decision-making basis, decision tree can be used to answer yes and no problem, it through the tree structure of the various situations are represented, each branch represents a choice (select Yes or no), until all the choices are fini

The inverse propagation algorithm (back-propagtion algorithm), BP learning is a supervised learning algorithm, which is an important method of artificial neural network learning, which is often used to train feedforward multilayer perceptron neural networks.First, the principle of BP learning1. Feed-forward neural networkRefers to the network in the processing of

11.1 What to do first11.2 Error AnalysisError measurement for class 11.3 skew11.4 The tradeoff between recall and precision11.5 Machine-Learning data 11.1 what to do firstIn the next video, I'll talk about the design of the machine learning system. These videos will talk about the major problems you will encounter when designing a complex machine learning s

Learning PHP focuses on sticking to the discussion and learning php methods. I believe that choosing a language is not based on its background and long history, but more importantly, its practicality. even if it is a brilliant history, I believe that you have chosen a language instead of looking at its background and long history. What's more important is its practicality, the flashy language, even if it is

First, bulk learningIn the bulk method of supervised learning, the adjustment of the prominent weights of multilayer perceptron occurs after all n examples of the training sample set , which constitute a round of training. In other words, the cost function of bulk learning is defined by the average error energy. The synaptic value adjustment of multilayer Perceptron is based on round-turn . Accordingly, a

Background:As a programmer, the technology around us is constantly being upgraded.Take the web, the first only HTML, then have CSS, and then have Ajax and so on. Now the total amount of knowledge accumulated in web development is very large. So much knowledge to learn swarmed, it is easy to let us at a loss, do not know where to learn from, like a headless fly.Recently, there have been other lab classmates came to me to ask how to get started a new field, but also found their roommates all day w

This article from http://blog.sina.com.cn/s/blog_80e381d101015fza.html1 Overview This article shows that the performance of the second-class classifier can be achieved through unlabeled dataStructuredTo improve the processing process, that is, if you know that the tag of a sample has restrictions on the tag of other samples, then the data is structured. In this paper, we propose that P-N learning uses labeled and unlabeled samples to train the second-

the similarities between practicing playing basketball and learning experience in a teacher's blog?In fact, I think learning every skill is connected. The 1th is to let oneself interested in this skill, have interest, will greatly increase the initiative of learning. 2nd, the acquisition of each skill needs a lot of practice, quantitative change is the precondit

20165316 Skills Learning experience and C language learning one, skills learning experiencesI can play ping-pong, in China, I can only say I "will" play, as to "better than most people" I dare not assert, because I do not feel the table tennis circle is far deeper than I imagined. However, I think the process of table tennis