Coursera 吴恩达 Machine Learning 课程 week 6 quiz

编程作业代码 GitHub 地址：https://github.com/coco-1998-2/Andrew-NG-Machine-Learning-Coursera

100%本地运行通过，不要直接抄，debug有问题的时候参考下就好。若是感觉有用，别忘记Star哦～

 

课程内嵌练习：

 

Machine Learning System Design 

 

 

C不应该选

 As we saw with neural networks, polynomial features can still be insufficient to capture the complexity of the data, especially if the features are very high-dimensional. Instead, you should use a complex model with many parameters to fit to the large training set.

 

 

 

Data for Machine Learning：

Having a large training set can help significantly improve a learning algorithm’s performance. However, the large training set is unlikely to help when:

（A）The features x do not contain enough information to predict y accurately (such as predicting a house’s price from only its size), and we are using a simple learning algorithm such as logistic regression.

（B）We are using a learning algorithm with a large number of features (i.e. one with “low bias”).

（C）The features x do not contain enough information to predict y accurately (such as predicting a house’s price from only its size), even if we are using a neural network with a large number of hidden units.

（D）We are not using regularization (e.g. the regularization parameter λ = 0).

正确选项：AC