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该资源为2011-2018年南京航空航天大学431金融学综合考研真题及部分答案解析，资源高清无水印哦！

Programming Exercise 1: Linear Regression Machine Learning Introduction In this exercise, you will implement linear regression and get to see it work on data. Before starting on this programming exercise, we strongly recom- mend watching the video lectures and completing the review questions for the associated topics. To get started with the exercise, you will need to download the starter code and unzip its contents to the directory where you wish to complete the exercise. If needed, use the cd command in Octave/MATLAB to change to this directory before starting this exercise. You can also find instructions for installing Octave/MATLAB in the “En- vironment Setup Instructions” of the course website. Files included in this exercise ex1.m - Octave/MATLAB script that steps you through the exercise ex1 multi.m - Octave/MATLAB script for the later parts of the exercise ex1data1.txt - Dataset for linear regression with one variable ex1data2.txt - Dataset for linear regression with multiple variables submit.m - Submission script that sends your solutions to our servers [?] warmUpExercise.m - Simple example function in Octave/MATLAB [?] plotData.m - Function to display the dataset [?] computeCost.m - Function to compute the cost of linear regression [?] gradientDescent.m - Function to run gradient descent [†] computeCostMulti.m - Cost function for multiple variables [†] gradientDescentMulti.m - Gradient descent for multiple variables [†] featureNormalize.m - Function to normalize features [†] normalEqn.m - Function to compute the normal equations ? indicates files you will need to complete † indicates optional exercises

该资源为2011-2021年江西师范大学333教育综合考研真题及部分答案详解，资源高清无水印哦！

数字逻辑课件及部分答案为毛法尧编著的数字逻辑（高等教育出版社）

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软件工程（原书第10版） 没有中文版教辅，只有英文版教辅和答案，下载时请注意！

组合数学第四版部分答案richard

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