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C1000-059 Exam Questions & Answers

Exam Code: C1000-059

Exam Name: IBM AI Enterprise Workflow V1 Data Science Specialist

Updated: Apr 09, 2024

Q&As: 62

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Practice These Free Questions and Answers to Pass the IBM Data and AI Exam

Questions 1

What is the goal of the backpropagation algorithm?

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

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Questions 2

What are two hyperparameters used when building a k-means model? (Choose two.)

A. kernel

B. learning rate

C. number of iterations

D. number of clusters

E. number of neighbors

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Questions 3

What are three elements that are typically part of a machine learning pipeline in scikit-learn or pyspark? (Choose three.)

A. model building

B. data preprocessing

C. model prediction

D. business understanding

E. use case selection F. data exploration

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Questions 4

Which two properties hold true for standardized variables (also known as z-score normalization)? (Choose two.)

A. standard deviation = 0.5

B. expected value = 0

C. expected value = 0.5

D. expected value = 1

E. standard deviation = 1

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Questions 5

What is the meaning of "deep" in deep learning?

A. To go deep into the loss function landscape.

B. The higher the number of machine learning algorithms that can be applied, the deeper is the learning.

C. A kind of deeper understanding achieved by any approach taken.

D. It indicates the many layers contributing to a model of the data.

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