课程信息
4.9
86,089 个评分
22,101 个审阅
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
完成时间(小时)

完成时间大约为55 小时

建议:7 hours/week...
可选语言

英语(English)

字幕:英语(English), 中文(简体), 希伯来语, 西班牙语(Spanish), 印地语, 日语...

您将获得的技能

Logistic RegressionArtificial Neural NetworkMachine Learning (ML) AlgorithmsMachine Learning
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
完成时间(小时)

完成时间大约为55 小时

建议:7 hours/week...
可选语言

英语(English)

字幕:英语(English), 中文(简体), 希伯来语, 西班牙语(Spanish), 印地语, 日语...

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 2 小时

Introduction

Welcome to Machine Learning! In this module, we introduce the core idea of teaching a computer to learn concepts using data—without being explicitly programmed. The Course Wiki is under construction. Please visit the resources tab for the most complete and up-to-date information....
Reading
5 个视频(共 42 分钟), 9 个阅读材料, 1 个测验
Video5 个视频
Welcome6分钟
What is Machine Learning?7分钟
Supervised Learning12分钟
Unsupervised Learning14分钟
Reading9 个阅读材料
Machine Learning Honor Code8分钟
What is Machine Learning?5分钟
How to Use Discussion Forums4分钟
Supervised Learning4分钟
Unsupervised Learning3分钟
Who are Mentors?3分钟
Get to Know Your Classmates8分钟
Frequently Asked Questions11分钟
Lecture Slides20分钟
Quiz1 个练习
Introduction10分钟
完成时间(小时)
完成时间为 2 小时

Linear Regression with One Variable

Linear regression predicts a real-valued output based on an input value. We discuss the application of linear regression to housing price prediction, present the notion of a cost function, and introduce the gradient descent method for learning....
Reading
7 个视频(共 70 分钟), 8 个阅读材料, 1 个测验
Video7 个视频
Cost Function8分钟
Cost Function - Intuition I11分钟
Cost Function - Intuition II8分钟
Gradient Descent11分钟
Gradient Descent Intuition11分钟
Gradient Descent For Linear Regression10分钟
Reading8 个阅读材料
Model Representation3分钟
Cost Function3分钟
Cost Function - Intuition I4分钟
Cost Function - Intuition II3分钟
Gradient Descent3分钟
Gradient Descent Intuition3分钟
Gradient Descent For Linear Regression6分钟
Lecture Slides20分钟
Quiz1 个练习
Linear Regression with One Variable10分钟
完成时间(小时)
完成时间为 2 小时

Linear Algebra Review

This optional module provides a refresher on linear algebra concepts. Basic understanding of linear algebra is necessary for the rest of the course, especially as we begin to cover models with multiple variables....
Reading
6 个视频(共 61 分钟), 7 个阅读材料, 1 个测验
Video6 个视频
Addition and Scalar Multiplication6分钟
Matrix Vector Multiplication13分钟
Matrix Matrix Multiplication11分钟
Matrix Multiplication Properties9分钟
Inverse and Transpose11分钟
Reading7 个阅读材料
Matrices and Vectors2分钟
Addition and Scalar Multiplication3分钟
Matrix Vector Multiplication2分钟
Matrix Matrix Multiplication2分钟
Matrix Multiplication Properties2分钟
Inverse and Transpose3分钟
Lecture Slides10分钟
Quiz1 个练习
Linear Algebra10分钟
2
完成时间(小时)
完成时间为 3 小时

Linear Regression with Multiple Variables

What if your input has more than one value? In this module, we show how linear regression can be extended to accommodate multiple input features. We also discuss best practices for implementing linear regression....
Reading
8 个视频(共 65 分钟), 16 个阅读材料, 1 个测验
Video8 个视频
Gradient Descent for Multiple Variables5分钟
Gradient Descent in Practice I - Feature Scaling8分钟
Gradient Descent in Practice II - Learning Rate8分钟
Features and Polynomial Regression7分钟
Normal Equation16分钟
Normal Equation Noninvertibility5分钟
Working on and Submitting Programming Assignments3分钟
Reading16 个阅读材料
Setting Up Your Programming Assignment Environment8分钟
Accessing MATLAB Online and Uploading the Exercise Files3分钟
Installing Octave on Windows3分钟
Installing Octave on Mac OS X (10.10 Yosemite and 10.9 Mavericks and Later)10分钟
Installing Octave on Mac OS X (10.8 Mountain Lion and Earlier)3分钟
Installing Octave on GNU/Linux7分钟
More Octave/MATLAB resources10分钟
Multiple Features3分钟
Gradient Descent For Multiple Variables2分钟
Gradient Descent in Practice I - Feature Scaling3分钟
Gradient Descent in Practice II - Learning Rate4分钟
Features and Polynomial Regression3分钟
Normal Equation3分钟
Normal Equation Noninvertibility2分钟
Programming tips from Mentors10分钟
Lecture Slides20分钟
Quiz1 个练习
Linear Regression with Multiple Variables10分钟
完成时间(小时)
完成时间为 5 小时

Octave/Matlab Tutorial

This course includes programming assignments designed to help you understand how to implement the learning algorithms in practice. To complete the programming assignments, you will need to use Octave or MATLAB. This module introduces Octave/Matlab and shows you how to submit an assignment....
Reading
6 个视频(共 80 分钟), 1 个阅读材料, 2 个测验
Video6 个视频
Moving Data Around16分钟
Computing on Data13分钟
Plotting Data9分钟
Control Statements: for, while, if statement12分钟
Vectorization13分钟
Reading1 个阅读材料
Lecture Slides10分钟
Quiz1 个练习
Octave/Matlab Tutorial10分钟
3
完成时间(小时)
完成时间为 2 小时

Logistic Regression

Logistic regression is a method for classifying data into discrete outcomes. For example, we might use logistic regression to classify an email as spam or not spam. In this module, we introduce the notion of classification, the cost function for logistic regression, and the application of logistic regression to multi-class classification. ...
Reading
7 个视频(共 71 分钟), 8 个阅读材料, 1 个测验
Video7 个视频
Hypothesis Representation7分钟
Decision Boundary14分钟
Cost Function10分钟
Simplified Cost Function and Gradient Descent10分钟
Advanced Optimization14分钟
Multiclass Classification: One-vs-all6分钟
Reading8 个阅读材料
Classification2分钟
Hypothesis Representation3分钟
Decision Boundary3分钟
Cost Function3分钟
Simplified Cost Function and Gradient Descent3分钟
Advanced Optimization3分钟
Multiclass Classification: One-vs-all3分钟
Lecture Slides10分钟
Quiz1 个练习
Logistic Regression10分钟
完成时间(小时)
完成时间为 4 小时

Regularization

Machine learning models need to generalize well to new examples that the model has not seen in practice. In this module, we introduce regularization, which helps prevent models from overfitting the training data. ...
Reading
4 个视频(共 39 分钟), 5 个阅读材料, 2 个测验
Video4 个视频
Cost Function10分钟
Regularized Linear Regression10分钟
Regularized Logistic Regression8分钟
Reading5 个阅读材料
The Problem of Overfitting3分钟
Cost Function3分钟
Regularized Linear Regression3分钟
Regularized Logistic Regression3分钟
Lecture Slides10分钟
Quiz1 个练习
Regularization10分钟
4
完成时间(小时)
完成时间为 5 小时

Neural Networks: Representation

Neural networks is a model inspired by how the brain works. It is widely used today in many applications: when your phone interprets and understand your voice commands, it is likely that a neural network is helping to understand your speech; when you cash a check, the machines that automatically read the digits also use neural networks. ...
Reading
7 个视频(共 63 分钟), 6 个阅读材料, 2 个测验
Video7 个视频
Neurons and the Brain7分钟
Model Representation I12分钟
Model Representation II11分钟
Examples and Intuitions I7分钟
Examples and Intuitions II10分钟
Multiclass Classification3分钟
Reading6 个阅读材料
Model Representation I6分钟
Model Representation II6分钟
Examples and Intuitions I2分钟
Examples and Intuitions II3分钟
Multiclass Classification3分钟
Lecture Slides10分钟
Quiz1 个练习
Neural Networks: Representation10分钟
4.9
职业方向

39%

完成这些课程后已开始新的职业生涯
工作福利

83%

通过此课程获得实实在在的工作福利

热门审阅

创建者 SKOct 26th 2017

Amazing course for people looking to understand few important aspects of machine learning in terms of linear algebra and how the algorithms work! Definitely will help me in my future modelling efforts

创建者 PTSep 1st 2018

Sub title should be corrected. Since I'm not that good in English but I know when there're mis-traslated or wrong sub title. If you fix this problems , I thin it helps many students a lot. Thanks!!!!!

讲师

Avatar

Andrew Ng

CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain

关于 Stanford University

The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States....

常见问题

  • 注册以便获得证书后,您将有权访问所有视频、测验和编程作业(如果适用)。只有在您的班次开课之后,才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程,可能无法访问某些作业。

  • 您购买证书后,将有权访问所有课程材料,包括评分作业。完成课程后,您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

还有其他问题吗?请访问 学生帮助中心