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IBM Data and AI: Data and AI IBM AI Enterprise Workflow V1 Data Science Specialist

IBM AI Enterprise Workflow V1 Data Science Specialist

Last Update May 3, 2024
Total Questions : 62

To help you prepare for the C1000-059 IBM exam, we are offering free C1000-059 IBM exam questions. All you need to do is sign up, provide your details, and prepare with the free C1000-059 practice questions. Once you have done that, you will have access to the entire pool of IBM AI Enterprise Workflow V1 Data Science Specialist C1000-059 test questions which will help you better prepare for the exam. Additionally, you can also find a range of IBM AI Enterprise Workflow V1 Data Science Specialist resources online to help you better understand the topics covered on the exam, such as IBM AI Enterprise Workflow V1 Data Science Specialist C1000-059 video tutorials, blogs, study guides, and more. Additionally, you can also practice with realistic IBM C1000-059 exam simulations and get feedback on your progress. Finally, you can also share your progress with friends and family and get encouragement and support from them.

Questions 4

What is the goal of the backpropagation algorithm?

Options:

A.  

to randomize the trajectory of the neural network parameters during training

B.  

to smooth the gradient of the loss function in order to avoid getting trapped in small local minimas

C.  

to scale the gradient descent step in proportion to the gradient magnitude

D.  

to compute the gradient of the loss function with respect to the neural network parameters

Discussion 0
Questions 5

Given the following matrix multiplication:

Questions 5

What is the value of P?

Options:

A.  

–9

B.  

17

C.  

12

D.  

–7

Discussion 0
Questions 6

A classification task has examples that are labeled as belonging to one of two classes:

•90% of the examples belong to class-1

•10% belong to class-2

Which two techniques are appropriate to deal with the class imbalance? (Choose two.)

Options:

A.  

apply dimensionality reduction to the features before training

B.  

impose an additional cost on the model for making classification mistakes on the minority class during training

C.  

lower the detection threshold of the minority class after training

D.  

oversample the minority class and/or undersample the majority class

E.  

after training, divide the model accuracy of each class by the proportion that they represent in the dataset

Discussion 0
Questions 7

What is meant by part-of-speech tagging in the context of text analytics?

Options:

A.  

replaces words with synonyms, e g. answer for reply

B.  

translates word by word

C.  

finds the root word

D.  

determines the category of a word, e.g nouns

Discussion 0
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2024-04-29
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