best machine learning books 2017

)]=1 else:print "The word:%s is not in my vocabulary!" %word return returnvecdef TRAINNBC (trainsamples,traincategory): Numtrainsamp=len (Trainsamples) NumWords=len (train Samples[0]) pabusive=sum (traincategory)/float (numtrainsamp) #y =1 or 0 feature Count P0num=np.ones (numwords) P1NUM=NP.O NES (numwords) #y =1 or 0 category count P0numtotal=numwords p1numtotal=numwords for I in Range (Numtrainsamp): if Traincategory[i]==1:p0num+=trainsamples[i] P0numtotal+=sum (Trainsamples[i]) E

=linearr.predict (X_train) #基于训练集得到的线性y值Plt.figure ()Plt.scatter (x_train,y_train,color= ' green ') #原始训练集数据散点图Plt.plot (x_train,y_train_pred,color= ' black ', linewidth=4) #线性回归的拟合线Plt.title (' Train ') #标题Plt.show ()Y_test_pred=linearr.predict (X_test)Plt.scatter (x_test,y_test,color= ' green ') #绘制测试集数据散点图Plt.plot (x_test,y_test_pred,color= ' black ', linewidth=4) #基于线性回归的预测线Plt.title (' Test ')Plt.show ()Print (' mse= ', Sm.mean_squared_error (y_test,y_test_pred)) #MSE值Print (' r2= ', Sm.r2_

Overview photo OCR problem Description and Pipeline sliding Windows getting Lots of data and Artificial data ceiling analysis:what part of the Pipeline to work on Next Review Lecture Slides Quiz:Application:Photo OCR Conclusion Summary and Thank You Log 4/20/2017:1.1, 1.2; Note Ocr? ... Coursera-

the value is a non-leaf node (that is, an object reference), you can modify all the content underneath the node.Stacks and stacks are the most fundamental things that a program runs. A program can run without a heap, but not without a stack. The heap is a data storage service for the stack, and the heap is a shared memory. However, it is the idea of the separation of heaps and stacks that makes Java garbage collection possible.Java, the size of the stack is set by-XSS, when the stack of data st

Author: Thuy T. Pham Selected from the Heart of Kdnuggets Machine compilation participation: Wu Yu Artificial intelligence is becoming the basic technology for a new generation of technology change, but developing artificial intelligence programs for their applications and businesses from scratch is expensive and often difficult to achieve the performance they want, but fortunately we have a large number of Ready-to-use APIs available to use. These A

: matplotlib Annotation Matplotlib provides an annotation tool annotations, which can be used to add text annotations to data graphs. Annotations are usually used to interpret data. I didn't understand this code, so I only gave the code in the book. #-*-Coding: cp936-*-import matplotlib. pyplot as pltdecisionnode = dict (boxstyle = 'sawtooth ', Fc = '0. 8 ') leafnode = dict (boxstyle = 'round4', Fc = '0. 8 ') arrow_args = dict (arrowstyle =' The index method is used to find the index returne

(testfilelist) for I in range (mtest): filenamestr = testfilelist [I] filestr = filenamestr. split ('. ') [0] classstr = int (filestr. split ('_') [0]) vectorundertest = img2vector ('testdigits/% s' % filenamestr) classifierresult = classify0 (vectorundertest, trainingmat, hwlabels, 3) print 'the classifier came back with: % d, the real Nswer is: % d' % (classifierresult, classstr) if (classifierresult! = Classstr): errorcount ++ = 1.0 print "\ nthe total numbers of errors is: % d" % errorcount

= Filenamestr.split ('. ') [0] classstr = Int (Filestr.split ('_') [0]) hwlabels.append (CLASSSTR) #測试例子标签 TRAININGM At[i,:] = Img2vector (' trainingdigits/%s '% filenamestr) testfilelist = Listdir (' testdigits ') errorcount = 0.0 mTe st = Len (testfilelist) for I in Range (mtest): Filenamestr = testfilelist[i] Filestr = Filenamestr.split (' .') [0] classstr = Int (Filestr.split ('_') [0]) Vectorundertest = Img2vector (' testdigits/%s '% filenamestr) Classifierresult = Classify0 (Vector

The first contact with SVM was still four years ago. At that time, it was used for handwritten digital recognition. Based on some books and literature, MATLAB was used to extract the PCA + SVMCode, The recognition rate is normal, 90 is not on, sorry to say hello to people. Most importantly, when I attended an interview, I was asked that Shenma is a support vector and I couldn't answer it. After being a graduate student, I learned this classic story re

understand computer knowledge, psychology and philosophy. Artificial intelligence consists of a very wide range of sciences, consisting of a variety of fields, such as machine learning, computer vision, and so on, in general, one of the main goals of AI research is to make machines capable of doing complex work that normally requires human intelligence. But different times, different people's understanding

), though it's no better than Microsoft's Visual Studio, but it's much more than the one that comes with it-if it's written in C, Helpless is written in Java, startup speed huge slow ~ ~Recently turned over the book "Machine Learning in Action". The book uses Python to implement some machine learning algorithms. I want

Advice for students of machine learningWritten by David MimnoOne of my students recently asked me for advice on learning ML. Here's what I wrote. It ' s biased toward my own experience, but should generalize.My Current Favorite Introduction is Kevin Murphy's book (Machine learning). Might also want to look at

Review and summary of the related articles on generative antagonism learning (generative adversarial network, GAN). Article: Generative adversarial Nets (2014) [Paper][code]Ian Goodfellow's first article about generative confrontation learning, groundbreaking work.-This paper proposes to estimate the generation model by the confrontation network.-The theory expounds the loss function of the model and its tr

Huadian North Wind BlowsKey laboratory of cognitive computing and application, Tianjin UniversityModification Date: 2015/8/15 Decision tree is a very simple machine learning classification algorithm. The decision tree idea comes from the human decision-making process. For the simplest example, when humans find it raining, they tend to have an easterly wind and then darken the sky. Corresponding to the decis