Most Recent IBM C1000-059 Exam Dumps

Prepare for the IBM AI Enterprise Workflow V1 Data Science Specialist exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.

QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the IBM C1000-059 exam and achieve success.

The questions for C1000-059 were last updated on Feb 19, 2025.

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Question No. 1

When should median value be used instead of mean value for imputing missing data?

Afor skewed data

Bfor real numbers

Cfor normally distributed data

Dfor large data sets

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Correct Answer: D

Question No. 2

A neural network is trained for a classification task. During training, you monitor the loss function for the train dataset and the validation dataset, along with the accuracy for the validation dataset. The goal is to get an accuracy of 95%.

From the graph, what modification would be appropriate to improve the performance of the model?

Aincrease the depth of the neural network

Binsert a dropout layer in the neural network architecture

Cincrease the proportion of the train dataset by moving examples from the validation dataset to the train dataset

Drestart the training with a higher learning rate

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Correct Answer: D

Question No. 3

Which measure can be used to show business stakeholders the likelihood that a machine learning model will generate a true prediction?

Aaccuracy

Bvariance

Cmean

Dskewness

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Correct Answer: A

Question No. 4

Which fine-tuning technique does not optimize the hyperparameters of a machine learning model?

Agrid search

Bpopulation based training

Crandom search

Dhyperband

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Correct Answer: D

Question No. 5

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

Amodel building

Bdata preprocessing

Cmodel prediction

Dbusiness understanding

Euse case selection

Fdata exploration

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Correct Answer: B, C, F

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