Support Vector Machine (large margin classifiers ) 1. cost function and hypothesis 下面那个紫色线就是SVM 的cost function       2. SVM 的数学解释                           3. SVM with kernel 我的理解是 kernel 的作用就是把低维度的 x 转化成高维的 f, 然后就好分类了   note: 上图就是一个2维(x1, x2)变3维(f1,…

  Basic theory (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks, )  regression, classification. (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, dee…

https://www.coursera.org/learn/machine-learning/exam/7pytE/linear-regression-with-multiple-variables 1. Suppose m=4 students have taken some class, and the class had a midterm exam and a final exam. You have collected a dataset of their scores on the…

在WEEK 5中,作业要求完成通过神经网络(NN)实现多分类的逻辑回归(MULTI-CLASS LOGISTIC REGRESSION)的监督学习(SUOERVISED LEARNING)来识别阿拉伯数字.作业主要目的是感受如何在NN中求代价函数(COST FUNCTION)和其假设函数中各个参量(THETA)的求导值(GRADIENT DERIVATIVE)(利用BACKPROPAGGATION). 难度不高,但问题是你要习惯使用MATLAB的矩阵QAQ,作为一名蒟蒻,我已经狗带了.以下代核心…

Question 1 Consider the problem of predicting how well a student does in her second year of college/university, given how well they did in their first year. Specifically, let x be equal to the number of "A" grades (including A-. A and A+ grades)…

  Algorithm:     When to select Anonaly detection or Supervised learning? 总的来说guideline是如果positive example (anomaly examples)特别少就用Anamaly detection. 如果数据positive example 越来越多,可以选择从Anomanly detection 切换到 Supervised learning.     怎么选择feature ?   可以先画出f…

Neural Network Motivations 想要拟合一条曲线,在feature 很多的情况下,feature的组合也很多,在现实中不适用,比如在computer vision问题中feature就太多了. Applications cost function and BP                 Gradient Checking https://www.coursera.org/learn/machine-learning/supplement/pjdBA/backpropa…

必做: [*] 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 1.warmUpE…

https://www.coursera.org/learn/machine-learning/exam/dbM1J/octave-matlab-tutorial Octave Tutorial 5 试题 1. Suppose I first execute the following Octave commands: A = [1 2; 3 4; 5 6]; B = [1 2 3; 4 5 6]; Which of the following are then valid Octave com…

Github地址:https://github.com/edward0130/Coursera-ML…