Coursera-MachineLearning-Week1题目整理 ''编号按照对应的内容,1-1代表第一大部分遇到的第一题,R代表Review,C代表运行的代码(Code)。 1-1. 解:计算机的经验E,任务T,标准P。我们在垃圾邮件分类时,我们的任务T就是区分邮件是垃圾邮件还是不是垃圾邮件。 1-2. 解: 任务1:你有大量相同物品的库存。你想预测在...
编号按照对应的内容,1-1代表第一大部分遇到的第一题,R代表Review,C代表运行的代码(Code)。 1-1 解:ABC A:无监督学习数据集不带有标签,正确。 B:聚类是无监督学习的一种,正确。 C:无监督学习可以寻找数据中的结构,正确。 D:聚类不是唯一的无监督学习算法,错误。 1-2 解:ABD 一号样本和二号样本被分到3...
课程首页:Coursera-Stanford-Machine Learning 授课教授:吴恩达(Andrew Ng) Week 1 2018.10.10 Introduction Linear Regression with One Variable Linear Algebra Review 1
The convenience and flexibility oflearning at your own paceare ideal for those who are pressed for time because of other equally important priorities. Also, Coursera offers a mobile app, so you can do some of your coursework while you're on the go, or even just review what you have alread...
-Build a classification model to predict sentiment in a product review dataset. -Analyze financial data to predict loan defaults. -Use techniques for handling missing data. -Evaluate your models using precision-recall metrics. -Implement these techniques in Python (or in the language of your choice...
https://www.coursera.org/learn/machine-learning Schedule: Week 1 - Due 07/04:DONE Introduction Linear regression with one variable Linear Algebra review (Optional) Week 2 - Due 07/11:DONE Linear regression with multiple variables Octave tutorial ...
Coursera Machine Learning By Prof. Andrew Ng. Contribute to vkosuri/CourseraMachineLearning development by creating an account on GitHub.
Machine Learningfrom Stanford University. Learning How to Learn: Powerful Mental Tools to Help You Master Tough Subjectsfrom The University of California, San Diego. The Science of Well-Beingfrom Yale University. Bitcoin and Cryptocurrency Technologiesfrom Princeton University. ...
Learning tough skills doesn’t happen over the course of days or weeks or months. Years is the right timeframe for most things. I wanted to know how quickly how quickly I could learn all of the math concepts behind machine learning: calculus, linear algebra, pro...
1. Machine Learning (Stanford) 《机器学习》 斯坦福大学 2. Learning How to Learn: Powerful mental tools to help you master tough subjects (McMaster University and UC San Diego) 《学习如何学习:强大的精神工具助你一臂之力》 加州大学圣地亚哥分校 ...