Most Recent IBM C1000-059 Exam Questions & Answers

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 Nov 20, 2024.

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Question No. 1

Considering one ML application is deployed using Kubernetes, its output depends on the data which is constantly stored in the model, if needing to scale the system based on available CPUs, what feature should be enabled?

Apersistent storage

Bvertical pod autoscaling

Chorizontal pod autoscaling

Dnode self-registration mode

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Correct Answer: A

Question No. 2

With the help of AI algorithms, which type of analytics can help organizations make decisions based on facts and probability-weighted projections?

Aprescriptive analytics

Bcognitive analytics

Cpredictive analytics

Ddescriptive analytics

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Correct Answer: A

Question No. 3

A data scientist is exploring transaction data from a chain of stores with several locations. The data includes store number, date of sale, and purchase amount.

If the data scientist wants to compare total monthly sales between stores, which two options would be good ways to aggregate the data? (Choose two.)

AFind the sum of the transaction prices

BSelect the largest transaction amount by month and store

CWrite a GROUP BY query

DPlot a time series plot of transaction amounts

EGenerate a pivot table

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Correct Answer: B, D

Question No. 4

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

ATo go deep into the loss function landscape.

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

CA kind of deeper understanding achieved by any approach taken.

DIt indicates the many layers contributing to a model of the data.

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Correct Answer: D

Question No. 5

What are the various components that make up a time series data?

Atrend, noise, covariance

Btrend, noise, kurtosis

Ctrend, seasonality, causation

Dtrend, seasonality, noise

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Correct Answer: D

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