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The article is from Professor Andrew Ng of Stanford University's machine learning course, which is a personal study note for the course, subject to the contents of the original course. Thank Bo Master Rachel Zhang's personal notes, for me to do personal study notes provide a

Long time no See, Hulu machine learning questions and Answers series and updated again!You can click "Machine Learning" in the menu bar to review all the previous installments of this series and leave a message to express your thoughts and ideas, and perhaps see your testimonials in the next article.Today's theme is"Di

million points to find an optimal hyper-plane, where there are 100 supporting vectors, then I just need to remember the information of these 100 points, and for subsequent classifications it is only necessary to use these 100 points instead of all 1 million points for calculation. Of course, in addition to the "memory-based learning" algorithm such as K-nearest neighbor, usually the algorithm does not dire

Welcome reprint, Reprint Please specify: This article from Bin column Blog.csdn.net/xbinworld.Technical Exchange QQ Group: 433250724, Welcome to the algorithm, technology, application interested students to join.Recently, while reviewing the classical machine learning algorithms, we also looked at some typical algorithms of deep learning. Deep

As a novice in machine learning, Stanford University Professor Wunda's "Machine learning" video course really attracts the beginner's interest and explains the various concepts. Take this series of blogs to record the core points of knowledge in each chapter. Chapter I.

In-depth spark machine learning combat (user behavior analysis)Course View Address: http://www.xuetuwuyou.com/course/144The course out of self-study, worry-free network: http://www.xuetuwuyou.comI. Objectives of the courseMaster the various operations of sparksql in-depth un

emerging. The text of the formula looks a bit around, below I send a detailed calculation process diagram.Refer to this: Http://www.myreaders.info/03_Back_Propagation_Network.pdf I did the finishing Here is the calculation of a record, immediately update the weight, after each calculation of a piece is immediately updated weight. In fact, the effect of batch update is better, the method is not to update the weight of the case, the record set of each record is calculated once, the added valu

Discovering and exploring data using advanced analytic algorithms such as large-scale machine learning, graphical analysis, statistical modelling, and so on is a popular idea, and in the IDF16 technology class, Intel software Development Engineer Wang Yiheng shares the course on machine

crawler Introduction, do not have to read too many books, online resources a lot of, of course, my csdn web crawler column , or quite popular:Tutorial Address: Click to viewBook Resources recommended:1. Want to learn the network crawler system, see "Python data collection " is a good choice (password: 2a69):Click to downloadMachine learning:Network Video recommendation: Wunda Teacher's machine

Summary:Classification and Regression tree (CART) is an important machine learning algorithm that can be used to create a classification tree (classification trees) or to create a regression tree (Regression tree). This paper introduces the principle of cart used for discrete label classification decision and continuous feature regression. The decision tree creation process analyzes the information Chaos Me

condition may be that the K-means fall into a bad local optimal.Some other ways to see Wikipedia.Of course, we should sometimes determine the value of k based on subsequent purposes (Later/downstream purpose). Or based on the height and weight of the people to divide the size of T-shirts, for example, if we want to divide the T-shirt size into 3 types of s/m/l, then the value of k should be 3; If you want to divide into 5 types of XS/S/M/L/XL, then t

efficiency and classification effect.A popular approach is to use evolutionary algorithms to optimize feature ranges.A suitable K-value selection, through a variety of heuristic algorithms.Both classification and regression are weighted according to distance measurements, making the neighboring values more average.SummarizeKNN algorithm is the simplest and most effective algorithm for classifying data, which can help us to quickly understand the basic model of classification algorithm in superv

, produced by the model.–for regression, is often a sensible measure of the discrepancy.–for classification There is other measures that is generally more sensible (they also work better).Reinforcement learningCombinatorial reinforcement learning, the output is a action or sequence of actions and the only supervisory signal are an Occasiona L scalar reward., haven goal in selecting each action was to maximize the expected sum of the future rewards.–we

Link (Chapter 1~12):Https://gallery.mailchimp.com/dc3a7ef4d750c0abfc19202a3/files/Machine_Learning_Yearning_V0.5_01.pdfLinks (Chapter 13th):Https://gallery.mailchimp.com/dc3a7ef4d750c0abfc19202a3/files/Machine_Learning_Yearning_V0.5_02.pdfLinks (chapter 14th):Https://gallery.mailchimp.com/dc3a7ef4d750c0abfc19202a3/files/Machine_Learning_Yearning_V0.5_03.pdfThis article has reprinted : http://blog.csdn.net/u014380165/article/details/73611858Mly--1. Why Machin