[Oct-2021] Verified IBM Exam Dumps with C1000-059 Exam Study Guide
Best Quality IBM C1000-059 Exam Questions ExamPrepAway Realistic Practice Exams [2021]
NEW QUESTION 11
What are three elements that are typically part of a machine learning pipeline in scikit-learn or pyspark?
(Choose three.)
- A. data preprocessing
- B. model building
- C. model prediction
- D. business understanding
- E. use case selection
- F. data exploration
Answer: A,C,F
NEW QUESTION 12
Which is a technique that automates the handling of categorical variables?
- A. decoding
- B. binary encoding
- C. one-hot encoding
- D. autoencoding
Answer: C
NEW QUESTION 13
A new test to diagnose a disease is evaluated on 1152 people, and 106 people have the disease, and 1046 people do not have the disease. The test results are summarized below:
In this sample, how many cases are false positives and false negatives?
- A. 73 false positives and 81 false negatives
- B. 81 false positives and 33 false negatives
- C. 81 false positives and 73 false negatives
- D. 33 false positives and 81 false negatives
Answer: D
NEW QUESTION 14
What is a class of machine learning problems where the algorithm is given feedback in the form of positive or negative reward in a dynamic environment?
- A. dynamic programming
- B. reinforcement learning
- C. reward learning
- D. feedback-based optimization
Answer: B
NEW QUESTION 15
Which is a preferred approach for simplifying the data transformation steps in machine learning model management and maintenance?
- A. Leverage only deep learning algorithms.
- B. Implement data transformation, feature extraction, feature engineering, and imputation algorithms in one single pipeline.
- C. Do not apply any data transformation or feature extraction or feature engineering steps.
- D. Apply a limited number of data transformation steps from a pre-defined catalog of possible operations independent of the machine learning use case.
Answer: C
NEW QUESTION 16
What are two hyperparameters used when building a k-means model? (Choose two.)
- A. number of iterations
- B. number of neighbors
- C. learning rate
- D. number of clusters
- E. kernel
Answer: A,D
NEW QUESTION 17
What is the technique called for vectorizing text data which matches the words in different sentences to determine if the sentences are similar?
- A. Sack of Sentences
- B. Cup of Vectors
- C. Bag of Words
- D. Box of Lexicon
Answer: C
NEW QUESTION 18
What is a class of machine learning problems where the algorithm builds a mathematical model from a set of data that contains both the inputs and the desired outputs?
- A. reinforcement learning
- B. supervised learning
- C. mentoring
- D. unsupervised learning
Answer: B
NEW QUESTION 19
In machine vision, the algorithm for detecting objects or features in an image based on a target pattern is known as?
- A. OCR
- B. normalized correlation
- C. Hough transformation
- D. Fourier transform
Answer: B
NEW QUESTION 20
A data analyst creates a term-document matrix for the following sentence: I saw a cat, a dog and another cat.
Assuming they used a binary vectorizer, what is the resulting weight for the word cat?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: B
NEW QUESTION 21
What is the meaning of "deep" in deep learning?
- A. The higher the number of machine learning algorithms that can be applied, the deeper is the learning.
- B. A kind of deeper understanding achieved by any approach taken.
- C. It indicates the many layers contributing to a model of the data.
- D. To go deep into the loss function landscape.
Answer: C
NEW QUESTION 22
What is the primary role of a data steward?
- A. they have a strong understanding of the enterprise's database architecture
- B. they are a "blue sky thinker" who comes up with new approaches to use new data in innovative ways
- C. the one who collects, processes, and performs statistical analysis on data
- D. they define data processes to meet compliance and regulatory obligations
Answer: C
NEW QUESTION 23
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.)
- A. Plot a time series plot of transaction amounts
- B. Generate a pivot table
- C. Select the largest transaction amount by month and store
- D. Find the sum of the transaction prices
- E. Write a GROUP BY query
Answer: A,C
NEW QUESTION 24
Which two statements are correct about deploying machine learning models? (Choose two.)
- A. It makes it possible to create reports for management dynamically using specific parameters from executives.
- B. It allows integration within business applications.
- C. It is critical for achieving high accuracy in training.
- D. It is a necessary step in training and evaluating the performance of the models.
- E. It is only possible on the cloud because they require a large amount of compute resources.
Answer: C,D
NEW QUESTION 25
What is meant by part-of-speech tagging in the context of text analytics?
- A. translates word by word
- B. determines the category of a word, e.g nouns
- C. finds the root word
- D. replaces words with synonyms, e g. answer for reply
Answer: B
NEW QUESTION 26
Which test is applied to determine the relationship between two categorical variables?
- A. z test
- B. t-test
- C. chi squared test
- D. paired t-test
Answer: C
NEW QUESTION 27
Which statement is true in the context of evaluating metrics for machine learning algorithms?
- A. A random classifier has AUC (the area under ROC curve) of 0.5
- B. Recall of 1 (100%) is always a good result
- C. Using only one evaluation metric is sufficient
- D. The F-score is always equal to precision
Answer: C
NEW QUESTION 28
Which distance is applied for multivariate outlier detection?
- A. Mahalanobis distance
- B. Minkowski distance
- C. Euclidean distance
- D. Manhattan distance
Answer: A
NEW QUESTION 29
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?
- A. increase the depth of the neural network
- B. restart the training with a higher learning rate
- C. insert a dropout layer in the neural network architecture
- D. increase the proportion of the train dataset by moving examples from the validation dataset to the train dataset
Answer: B
NEW QUESTION 30
The least squares optimization technique (The Method of Least Squares) is used in which algorithm?
- A. Logistic regression
- B. Linear regression
- C. Naive Bayes classification
- D. Support Vector Machines
Answer: B
NEW QUESTION 31
Select the three computing languages that IBM Cloud Object Storage SDK supports. (Choose three.)
- A. Node.js
- B. Python
- C. C/C++
- D. PHP
- E. Java
- F. Swift
Answer: A,B,E
NEW QUESTION 32
What is the best step by step order for machine learning pipeline?
Answer:
Explanation:
NEW QUESTION 33
Which fine-tuning technique does not optimize the hyperparameters of a machine learning model?
- A. grid search
- B. random search
- C. population based training
- D. hyperband
Answer: D
NEW QUESTION 34
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