IBM C1000-059 IBM AI Enterprise Workflow V1 Data Science Specialist Exam Practice Test

for skewed data

for real numbers

for normally distributed data

for large data sets

It allows integration within business applications.

It makes it possible to create reports for management dynamically using specific parameters from executives.

It is critical for achieving high accuracy in training.

It is a necessary step in training and evaluating the performance of the models.

It is only possible on the cloud because they require a large amount of compute resources.

The use case requires a 100% likelihood of making a correct/true prediction.

Training and testing data for the model contain outliers.

Data for the machine learning model is available only as static CSV files.

The neural network for the model requires significantly more computing power than a logistic regression model.

It is encoding for Latin script.

It is rarely used today.

It is encoding for Unicode characters.

It is equal to ASCII.

64 inches and 74 inches

66.5 inches and 69 inches

71.5 inches and 76.5 inches

66.5 inches and 71.5 inches

Implement data transformation, feature extraction, feature engineering, and imputation algorithms in one single pipeline.

Do not apply any data transformation or feature extraction or feature engineering steps.

Leverage only deep learning algorithms.

Apply a limited number of data transformation steps from a pre-defined catalog of possible operations independent of the machine learning use case.

Naive Bayes can be used for regression.

Let p(C1 | x) and p(C2 | x) be the conditional probabilities that x belongs to class C1 and C2 respectively, in a binary model, log p (C1 | x) – log p(C2 | x) > 0 results in predicting that x belongs to C2.

Naive Bayes is a conditional probability model.

Naive Bayes doesn't require any assumptions about the distribution of values associated with each class.

methods that failed

newest developments in AI methods

benefits of cognitive over business analytics

realistic impact on the business measures

differences between cloud provider portfolios

alternative methods to address the business problem

replaces words with synonyms, e g. answer for reply

translates word by word

finds the root word

determines the category of a word, e.g nouns