coursera introduction to machine learning

returnITEMSCORES[:N]#returns the item name of the top N large score value, and its forecast score valueName the file svd2.py and enter it at the Python prompt:>>>Import svd2>>>testdata=svd2.loadexdata ()>>> Svd2.recommend (testdata,1,n=3,percentage=0.8) #对编号为1的用户推荐评分较高的3件商品Reference:1.Peter Harrington, "machine learning combat", people's post and Telecommunications press, 20132.HTTP://WWW.AMS.ORG/SAMPL

of finding the best fitting line is actually looking for the best b b and M M. In order to find the best fit line, here we first define what line is the best line. We define error (cost function): Error function errors (b,m) =1n∑1n ((B+MXI) −yi) 2 error functions \ error_{(b, M)}=\frac{1}{n}\sum_{1}^{n} ((b+mx_i)-y_i) ^{2} The Python code that calculates the loss function is as follows: # y = b + mx def compute_error_for_line_given_points (b, M, points): totalerror = SUM ((((b + M * point[

understand. Search, about half an hour can be thoroughly understood.Support Vector machines. SearchHttp://www.cnblogs.com/jerrylead/archive/2011/03/13/1982639.htmlAnd I like a lot of applications of wild programmers have resonance, even if 100 saw what I share a person has been harvested value.When I was young, I wanted to make weapons so that everyone could have the power to change the world, grow up for so many years, and know that things are going to die fast, sharing weapons is power, and s

maximum value of 3. Array ([[[2, 1, 2, 1], [0, 1, 2, 1], [2, 1, 0, 2]], [[0, 1, 0, 0], [1, 1, 2, 1], [1, 0, 1, 2]] Another example: Np.random.randint (3, 6, size=[2,3]) returns data with a dimension of 2x3. The value range is [3,6]. Array ([[4, 5, 3], [3, 4, 5]]) 4) Random_integers (low[, high, size]), similar to the above randint, the difference between the range of values is closed interval [low, high]. 5) Random_sample ([size]), returns the random floating-point number in the half-open inte

discriminant of a logistic regression, and the parameters of each intermediate node are recorded. So, for the Cbow model, there are:Then, the target function is:Then the parameters θ and x of the target function are updated by the random gradient descent method, so that the value of the objective function can be maximized.Similar to the Cbow model, Skip-gram is solved by optimizing the following objective functions.whichSo, the target function of Skip-gram is:The parameters θ and V (w) of the t

is to fit the distribution of training data, can we start with a sample from the beginning of Gibbs and then go through K-step to sampling, so that it converges to the target distribution faster? Based on this idea, Hinton invented the contrastive divergence algorithm in 2002, which usually results in 1 iterations, thus reducing the complexity of the RBM optimization problem.Finally, how do we evaluate the quality of the RBM model? For example, in the classification problem, we need to use the

MySpace qizmt is a mapreduce framework designed to run and develop distributed computing application projects running on Windows Server large-scale clusters. MySpace qizmt is an open-source framework initiated by MySpace to develop trustworthy, scalable, and super-Simple distributed application projects. Open Source Address: http://code.google.com/p/qizmt /. Infer. NET is an open-source framework that runs Bayesian inference in graphical mode. It is also used for ProbabilityProgramDesign. Open

matrix matrices, and the column represents the feature, where the percentage represents the variance ratio of the number of features required before taking the default to 0.9" "defPCA (datamat,percentage=0.9): #averaging for each column, because the mean value is subtracted from the calculation of the covarianceMeanvals=mean (datamat,axis=0) meanremoved=datamat-meanvals#CoV () Calculating varianceCovmat=cov (meanremoved,rowvar=0)#using the Eig () method in the module linalg for finding eigen

Efficiency comparison:It's a cliché, but this time with a new module,Run Time Test Module Timeti:1 ImportTimeit2 3normal = Timeit.timeit ('sum (x*x for x in range )', number=10000)4NATIVE_NP = Timeit.timeit ('sum (na*na)',#Repeating part5setup="import numpy as np; na = Np.arange (+)",#Setup runs only once6number=10000)#Number of repetitions7GOOD_NP = Timeit.timeit ('Na.dot (NA)',8setup="import numpy as np; na = Np.arange (+)",9number=10000)Ten One Print('Native Run time:', Normal,'\ n', A

Introduction to several common optimization algorithms for machine learning789491451. Gradient Descent method (Gradient descent) 2. Newton's method and Quasi-Newton method (Newton ' s method Quasi-Newton Methods) 3. Conjugate gradient method (conjugate Gradient) 4. Heuristic Optimization Method 5. Solving constrained optimization problems--Lagrange multiplier methodEach of us in our life or work encountere

Brief introduction In recent years, because of the cloud platform, large data, high-performance computing, machine learning and other areas of progress, artificial intelligence also fire up. Face recognition, speech recognition and other related functions have been proposed, but can form products and large-scale use of small. Because it is difficult for non-profe

http://mp.weixin.qq.com/s?__biz=MjAzNzMzNTkyMQ==mid=211346099idx=1sn= 41d9c9761e729ed57a89ae2aaaa66bb1scene=0#rdAbout the specific concept of machine learning and introduction, there are a lot of this information, if you are interested, you can go to see, here I will not repeat. In short, the machine

Gan Introduction Generativeadversarial Nets The idea of generating a confrontation network was put forward in 2014, in the original paper, the author uses game theory to explain the thought behind the Gan frame. Each Gan frame contains a generative model G and a discriminant model D, the task of which is to determine whether a given image looks ' natural ', in other words, as if it were a machine-generated.

Recently TalkingData Open source The main role of Fregata,fregata is to speed up the computing speed of machine learning based on spark, it is said that 1 billion * 1 billion level of data if cached in memory, the 1s clock can be completed, if not cached, 10 seconds to fix, If this is the case, it is a fortress, and the following are only translations, if there are incorrect welcome corrections Brief

Abu-mostafa is a teacher of Lin Huntian (HT Lin) and the course content of Lin is similar to this class.L 5. 2012 Kaiyu (Baidu) Zhang Yi (Rutgers) machine learning public classContent more suitable for advanced, course homepage @ Baidu Library, courseware [email protected] Dragon Star ProgramL prml/Introduction to machine