吴恩达机器学习作业以及作业课件

machine-learning-ex1 到machine-learning-ex8 里面作业部分已经完成并且有相应的注释

function J = computeCost（X y theta）
%线性回归算法
%COMPUTECOST Compute cost for linear regression
%   J = COMPUTECOST（X y theta） computes the cost of using theta as the
%   parameter for linear regression to fit the data points in X and y

% Initialize some useful values
m = length（y）; % number of training examples

% You need to return the following variables correctly 
J = 0;

% ====================== YOUR CODE HERE ======================
% Instructions: Compute the cost of a particular choice of theta
%               You should set J to the cost.
h = X*theta - y; %X*theta 为Hypothesis 
J = 1/（2*m） * sum（h.^2）;%Cost Function

% =========================================================================

end

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----
     目录           0  2018-07-17 23:02  machine-learning-ex1\
     目录           0  2017-03-20 13:48  machine-learning-ex1\machine-learning-ex1\
     目录           0  2018-07-27 15:21  machine-learning-ex1\machine-learning-ex1\ex1\
     文件         721  2018-07-27 10:43  machine-learning-ex1\machine-learning-ex1\ex1\computeCost.m
     文件         698  2018-07-27 15:21  machine-learning-ex1\machine-learning-ex1\ex1\computeCostMulti.m
     文件        4607  2018-07-27 13:52  machine-learning-ex1\machine-learning-ex1\ex1\ex1.m
     文件        4710  2018-07-27 10:08  machine-learning-ex1\machine-learning-ex1\ex1\ex1_multi.m
     文件        1359  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\ex1data1.txt
     文件         657  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\ex1data2.txt
     文件        1380  2018-07-27 15:21  machine-learning-ex1\machine-learning-ex1\ex1\featureNormalize.m
     文件        1402  2018-07-27 10:42  machine-learning-ex1\machine-learning-ex1\ex1\gradientDescent.m
     文件        1087  2018-07-27 10:13  machine-learning-ex1\machine-learning-ex1\ex1\gradientDescentMulti.m
     目录           0  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\
     目录           0  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\
     文件        1624  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\AUTHORS.txt
     文件        3862  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\ChangeLog.txt
     文件        1551  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\LICENSE_BSD.txt
     文件       19369  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\README.txt
     文件         881  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\jsonopt.m
     文件       18732  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\loadjson.m
     文件       15574  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\loadubjson.m
     文件         771  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\mergestruct.m
     文件       17462  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\savejson.m
     文件       16123  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\saveubjson.m
     文件        1094  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\jsonlab\varargin2struct.m
     文件        1195  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\makeValidFieldName.m
     文件        5562  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\lib\submitWithConfiguration.m
     文件         774  2018-07-27 15:21  machine-learning-ex1\machine-learning-ex1\ex1\normalEqn.m
     文件        1089  2018-07-27 10:42  machine-learning-ex1\machine-learning-ex1\ex1\plotData.m
     文件        1876  2017-03-14 09:40  machine-learning-ex1\machine-learning-ex1\ex1\submit.m
     文件         258  2018-07-27 10:14  machine-learning-ex1\machine-learning-ex1\ex1\token.mat
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