那么这里的computeCost函数给了3个参数X, y, theta,并没有给\theta_{0},经人提醒,其实\theta_{0}可以等于\theta_{1}乘以列向量中为1的元素, 这里的\theta_{1}其实就是参数\theta,即\theta_{0} = \theta * 1,a = [1,2,3,4] .* [1,2,3,4] = [1,4,9,16], 而sum(a) = 30 ,所以...
2-1-2 特征缩放 (1)什么是特征缩放 正如2-1-1所述,如果直接把特征1的范围0~2000、特征2的范围1~5拿来用,则会出现一条非常非常狭长的椭圆,这一点将对梯度下降法造成困难,使得梯度下降法的路径非常之复杂(四处乱走,正如上面第二幅图那张课件中红线画的那样)。 解决方案很简单,只需要令: x(i)1=size(fe...
Week 2 开始,Andrew带我们作了Octave实训,留了编程作业,课程从单变量线性回归升级到多变量,难度也有所增加。以下是部分笔记。 【一】Octave常用命令 (1)Basic operation 真值判断:等于不等于,或且非运算,结果是1 或者 0(例如1==2,true == false,true != false,true | false,true & false,~true) a = [...
Please note, there is no formal assignment this week, and we hope that everyone participates in the discussion instead. Week 3: Extended Linear Regression In this module, you will learn how to include categorical (discrete) inputs in your linear regression problem, as well as nonlinear effects...
computeCostMulti.m J=1/(2*m)*sum((X*theta-y).^2); featureNormalize.m mu=mean(X);%计算均值sigma=std(X,1,1);%计算标准差fori=1:size(X,2)%遍历所有列X_norm(:,i)=(X(:,i)-mu(i))./sigma(i);%进行标准化end normalEqn.m ...
This repository contains the answers for coursera 's "Databases and SQL for Data Science with Python " course by ibm with honors (week 1 - week 6) courseraibmcoursera-machine-learningcoursera-data-sciencecoursera-coursecoursera-assignmentcoursera-pythoncoursera-specializationcognitive-classcognitive-class...
In a world where data-driven solutions are revolutionizing industries, mastering advanced machine learning techniques is a pivotal skill that empowers innovation and strategic decision-making. This equips you with the expertise needed to harness advanced machine-learning algorithms. You will delve into ...
Programming Assignment Deep Q-Learning - Lunar Lander Certificate of Completion Specialization Certificate Course Review : This Course is a best place towards becoming a Machine Learning Engineer. Even if you're an expert, many algorithms are covered in depth such as decision trees which may help...
吴恩达深度学习2-Week3课后作业-Tensorflow 一、deeplearning-assignment 到目前为止,我们一直使用numpy来建立神经网络。这次作业将深入学习框架,可以更容易地建立神经网络。 TensorFlow,PaddlePaddle,Torch,Caffe,Keras等机器学习框架可以显著地加速机器学习开发。这些框架有很多文档,可以随意阅读。在本次任务中,将学习如何在Te...
Andrew Ng,class1,week1,assignment1 吴恩达deep Learning ,class1,week1,assignmen11.code 2.the understanding of logistic regression and the LOST FUNCTION,COST FUNCTION ①logistic regression ②sigmoid function and lost function ③cost function Coursera | Introduction to Data Science in Python(University ...