Sogou Machine learning practice guidelines: case analysis

The road has been the main mathematical series of post finishing book, please guidance.       "Machine learning practice guidelines: application case analysis" is rare in machine learning and data analysis in the field of a book, but also for the few existing a lot of practice, the application of case contains theory and algorithm analysis of the works, author for machine learning algorithms both abstract and complicated and involves many disciplines of Mathematics and the characteristics of, and strive to integrate theory with practice, always to algorithm is applied as the main line, from the shallow to the deep with a new point of view.
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Arduino essay (3)

Traffic lights //2016-4-12 Library is free / / This software you can redistribute it and/or; Modify it under the terms of / the GNU Lesser General Public License as published by the Free / Software Foundation...
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Arduino essay (2)

B_COLOR #define 10 G_COLOR #define 11 R_COLOR #define 12 Setup void () { PinMode (B_COLOR, OUTPUT); PinMode (G_COLOR, OUTPUT); PinMode (R_COLOR, OUTPUT); } Loop void () { DigitalWrite (B_COLOR, HIGH); ...
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Arduino essay (1)

Int ledPin=13; / / arudino plate with a small LED lights connected to the digital pin 13. Delaytime=200 //1s; int (seconds) is equal to 1000ms (MS) Setup void () { PinMode (ledPin, OUTPUT); } //http://prog3.com/sbdm/blog/myhaspl/ Loop void () {...
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Java- comparison sort and hash

Dplearn package; Java.util.Arrays import; Java.util.Collections import; Java.util.HashMap import; Java.util.Map import; Java.util.Set import; Class Learn public { Static void main public (String[]...
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Java container

Dplearn package; Java.util.ArrayList import; Java.util.Iterator import; Java.util.List import; Class Learn public { Static void main public (args String[]) { MyList=new ArrayList List (); Basicinf...
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Swift algorithm -10 notes

Http://prog3.com/sbdm/blog/myhaspl Func findnode private (val:Int) ->Bool{//http://prog3.com/sbdm/blog/myhaspl / / search node http://prog3.com/sbdm/blog/myhaspl Let mysltop if = slinktop{ My var...
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Swift algorithm -9 notes

ViewController: NSViewController class { Let trieroot:TrieNode private = TrieNode (str: "", NoteState.Root nstate:) Func viewDidLoad override () { Super.viewDidLoad () / /...
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Road of Mathematics (Machine Learning Practice Guide) - text mining with NLP (6)

Wordfeatures def (word): Return {"cnword": word} .... Classifier=nltk.NaiveBayesClassifier.train (samplewords) # university belongs to the category of http://prog3.com/sbdm/blog/myhaspl U print "---- the category of the University" Classifier.class print...
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Road of Mathematics (Machine Learning Practice Guide) - text mining with NLP (5)

# conditions at different frequencies, each entry in the frequency of classification Print "c" Cfd=nltk.ConditionalFreqDist (samplewords) Fdist=cfd[u''] Word in fdist: for Word print Print - "liquidity at times" Cfd[u'print financial'][u'...
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Swift algorithm -8 notes

Answer==nil{if / / calculation equation P0:Double=leftbound var! P1:Double=rightbound var! Q0:Double var = comresult (P0) Q1:Double var = comresult (P1) ...
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Swift algorithm -7 notes

Func compute @IBAction (AnyObject sender:) { / / 19*x^7-31*x^5+16*x^2+7*x-90=0 / / for one yuan equation Newton iteration method for solving the maximum range of [-100000100000]. 19*x^7-31*x^5+16*x^2+7*x-90= "mytitle.stringValue=...
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Road of Mathematics (Machine Learning Practice Guide) - text mining with NLP (4)

Sample=cutstring (U, "it is reported that this car is nicknamed the beast, the beast is likely to be used in January 2017 when the United States, the forty-fifth president of the United states. At present, the specifications for the beast belong to the top secret information, but the spy photos show beast by the Cadillac of the guard gate and headlight design. ") Tokenstr=nltk.word_tokenize (sample) Fdist3=nltk.FreqDist (tokenstr) Print "--- the number of times in the United States" Print...
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Road of Mathematics (Machine Learning Practice Guide) - text mining with NLP (3)

#--coding:utf-8-- By myhaspl #code __future__ import unicode_literals from __future__ Import Division from Nltk import Sys import Sys.path.append ("/") Jieba import Cutstring def (txt): # points...
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Road of Mathematics (Machine Learning Practice Guide) - text mining with NLP (2)

#--coding:utf-8-- By myhaspl #code __future__ import unicode_literals from __future__ Import Division from Nltk import Sys import Sys.path.append ("/") Jieba import Cutstring def (txt):...
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Road of Mathematics (Machine Learning Practice Guide) - text mining with NLP (1)

According to foreign p s media reports n, X America ns scientists n recently T V the UL2800 m million M (x $VN1.84 m billion M RMB n) x UJ of VN funds VN, X for V design VN a m V and P humans identify the N v n patterns, speed n comparable Z UJ computer system n intelligence agencies n to V with V UJ n data more and more d m, these x R n data are d must be d v to quickly analyze the ad...
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    A good book

    Machine learning practice guidelines have theory, there are code, there are explanations, there is actual combat, the goal is: to let beginners more and more clear, the more you want to see, read unknowingly easily entered the field of machine learning.
    Basics first foundation of mathematics and in the machine learning field of application about also recommended supporting the learning of math books, then use examples to illustrate the use of computing platform, using Python and R for language, explains the algorithm for image, information hiding, least squares fitting, frequency factor analysis, Euclidean distance, tells the reader how to use computing platform to complete the engineering application. Finally, through a large number of statistical analysis and machine learning case provides practice guidelines, first of all to explain regression analysis, interval distribution, graphical data, distribution trend, normal distribution, distribution fitting and data analysis, and then explain the neural network, statistical algorithm, Euclidean distance, cosine similarity, linear and nonlinear regression, data fitting, linear filtering, image recognition, face recognition, web page classification etc. machine learning algorithms.
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