Valid C1000-059 Exam Q&A PDF C1000-059 Dump is Ready (Updated 64 Questions)
Exam Questions and Answers for C1000-059 Study Guide
NEW QUESTION 34
In machine vision, the algorithm for detecting objects or features in an image based on a target pattern is known as?
- A. OCR
- B. Hough transformation
- C. Fourier transform
- D. normalized correlation
Answer: D
NEW QUESTION 35
What is the first step in creating a custom model in Watson Visual Recognition service?
- A. Use IBM SPSS to create new machine learning classifiers.
- B. Test the newly trained model.
- C. Document the errors from the built in models.
- D. Obtain image files containing objects to be classified and organize them into classes.
Answer: A
NEW QUESTION 36
When should median value be used instead of mean value for imputing missing data?
- A. for skewed data
- B. for real numbers
- C. for large data sets
- D. for normally distributed data
Answer: C
NEW QUESTION 37
Which situation would disqualify a machine learning system from being used for a particular use case?
- A. Data for the machine learning model is available only as static CSV files.
- B. The use case requires a 100% likelihood of making a correct/true prediction.
- C. The neural network for the model requires significantly more computing power than a logistic regression model.
- D. Training and testing data for the model contain outliers.
Answer: C
NEW QUESTION 38
What are three elements that are typically part of a machine learning pipeline in scikit-learn or pyspark?
(Choose three.)
- A. data exploration
- B. model building
- C. model prediction
- D. business understanding
- E. use case selection
- F. data preprocessing
Answer: A,C,F
NEW QUESTION 39
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?
- A. horizontal pod autoscaling
- B. persistent storage
- C. vertical pod autoscaling
- D. node self-registration mode
Answer: B
NEW QUESTION 40
What is the main difference between traditional programming and machine learning?
- A. Machine learning is optimized to run on parallel computing and cloud computing.
- B. Machine learning takes full advantage of SDKs and APIs.
- C. Machine learning does not require explicit coding of decision logic.
- D. Machine learning models take less time to train.
Answer: C
NEW QUESTION 41
Which is an example of a nominal scale data?
- A. a variable mood with a scale of values unhappy, ok, and happy
- B. a variable bank account balance whose possible values are $5, $10, and $15
- C. a variable temperature with a scale of values low, medium, and high
- D. a variable industry with categorical values such as financial, engineering, and retail
Answer: B
NEW QUESTION 42
Which distance is applied for multivariate outlier detection?
- A. Minkowski distance
- B. Manhattan distance
- C. Euclidean distance
- D. Mahalanobis distance
Answer: D
NEW QUESTION 43
Which is a technique that automates the handling of categorical variables?
- A. binary encoding
- B. decoding
- C. one-hot encoding
- D. autoencoding
Answer: C
NEW QUESTION 44
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 45
What are three operators used by genetic programming? (Choose three.)
- A. sheltering
- B. reciprocation
- C. crossover
- D. duel
- E. mutation
- F. selection
Answer: C,D,F
NEW QUESTION 46
Given the following sentence:
The dog jumps over a fence.
What would a vectorized version after common English stopword removal look like?
- A. ['dog', 'fence', 'run']
- B. ['a', 'dog', 'fence', 'jumps', 'over', 'the']
- C. ['fence', 'jumps']
- D. ['dog', 'fence', 'jumps']
Answer: D
NEW QUESTION 47
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. insert a dropout layer in the neural network architecture
- B. increase the proportion of the train dataset by moving examples from the validation dataset to the train dataset
- C. restart the training with a higher learning rate
- D. increase the depth of the neural network
Answer: C
NEW QUESTION 48
With the help of AI algorithms, which type of analytics can help organizations make decisions based on facts and probability-weighted projections?
- A. prescriptive analytics
- B. cognitive analytics
- C. descriptive analytics
- D. predictive analytics
Answer: A
NEW QUESTION 49
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