Question 1 (1 point) Saved In Al, one primary advantage of deep learning models is they can data. Therefore, inference ability is not needed. True False Question 2 (1 point) Saved 0-1 logic is a traditional Al problem. True False Question 3 (1 point) Saved Gradient descent is an optimization algorithm, and it can be used in li classification. True False aotian A11 min O Type here to search F C Question 4 (1 point) Saved In machine learning, a large learning rate will result in faster True False Question 5 (1 point) Saved The Iris dataset is a typical unstructured dataset. True False Question 6 (1 point) Saved Supervised learning uses labeled data to train machine learnir True False Question 10 (1 point) Saved The original hard-margin SVM is a typical method to solve non-linea problem. True False Question 11 (1 point) Saved Which one is a typical machine learning problem? supervised learning unsupervised learning reinforcement learning all of them Question 7 (1 point) Saved Logistic regression is a typical method for regression tasks. True False Question 8 (1 point) Saved In soft-margin SVM, a small C value will result in over-fitting. True False Question 9 (1 point) Saved Weight decay can be used as a regularizer to train machine learning mo True False en logistic regression, which one can be used as the function ? e^(-2) 01/(1+e^(-2) 1+e^(-z) 01/e^(-2) Question 14 (1 point) Saved Which one CANNOT be used for linear classification problem? linear regression logistic regression linear support vector machine none of them Question 15 (1 point) Saved In python sklearn package, which function is used to train a machine learr model, such as a SVM model? fit() search train() get() Question 16 (1 point) Saved In which area Al can be applied? Natural Language Processing Medical Image Analysis Type here to search n H! Question 16 (1 point) Saved In which area Al can be applied? Natural Language Processing Medical Image Analysis Customized Recommendation All of them Saved Question 17 (1 point) The following areas are closely tied to Al except Deep Learning Data Science SQL database Question 20 (1 point) Saved Which one is NOT an Al method? Web Neural network SVM Logistic regression Which one is NOT an Al method? Web Neural network SVM Logistic regression Question 18 (1 point) Saved Which option is NOT a hyper-parameter? number of training epochs learning rate model weight All of these options are hyper-parameters Question 19 (1 point) Saved In the hard-margin SVM, the optimization problem can be solved by Closed-form programming Step programming Quadratic programming Saved Question 16 (1 point) In which area Al can be applied? Natural Language Processing Medical Image Analysis Customized Recommendation All of them Question 17 (1 point) Saved The following areas are closely tied to Al except Deep Learning Data Science SQL database In python sklearn package, which function is used to train a machine learn model, such as a SVM model? fit() search train() get() Question 16 (1 point) Saved In which area Al can be applied? Natural Language Processing Medical Image Analysis In logistic regression, which one can be used as the function O e^(-2) 1/(1+e^(-z)) 1+e^(-2) w 1 / e^(-z) Saved Question 14 (1 point) Which one CANNOT be used for linear classification problem? linear regression logistic regression linear support vector machine none of them The original hard-margin SVM is a typical method to solve non-linear clas problem. True False Question 11 (1 point) Saved Which one is a typical machine learning problem? supervised learning unsupervised learning reinforcement learning all of them Question 12 (1 point) Saved Assuming X stands for a data point with m features, which method can be use Type here to search Logistic regression is a typical method for regression tasks. True False Question 8 (1 point) Saved In soft-margin SVM, a small C value will result in over-fitting. True False Question 9 (1 point) Saved Weight decay can be used as a regularizer to train machine learning mo True False Question 7 (1 point) Saved Logistic regression is a typical method for regression tasks. True False Question 8 (1 point) Saved In soft-margin SVM, a small C value will result in over-fitting. True False Question 9 (1 point) Saved Weight decay can be used as a regularizer to train machine learning mo True False in machine learning, a large learning rate will result in faster convergence. True False Question 5 (1 point) Saved The Iris dataset is a typical unstructured dataset, True False Question 6 (1 point) Saved Supervised learning uses labeled data to train machine learning models. True False tage of deep learning models is they can memorize the ce ability is not needed. Saved | Al problem. Saved optimization algorithm, and it can be used in linear n Al, one primary advantage of deep learning models is they can n data. Therefore, inference ability is not needed. True False Question 2 (1 point) Saved 0-1 logic is a traditional Al problem. True False Question 3 (1 point) Saved Gradient descent is an optimization algorithm, and it can be used in line classification. True False