Practice Free HPE2-T38 Exam Online Questions
What is the purpose of feature engineering in machine learning?
- A . To evaluate the performance of the machine learning model
- B . To clean and preprocess the data
- C . To create new features from existing ones
- D . To select the most relevant features for the model
C
Explanation:
The purpose of feature engineering in machine learning is to create new features from existing ones to improve the performance of the model.
Which of the following is NOT a common supervised learning algorithm?
- A . Support Vector Machines (SVM)
- B . K-Nearest Neighbors (KNN)
- C . Decision Trees
- D . K-Means Clustering
D
Explanation:
K-Means Clustering is not a common supervised learning algorithm, it is actually an unsupervised learning algorithm.
What is one of the key prerequisites for implementing an HPE machine learning solution?
- A . Ability to play a musical instrument
- B . Proficiency in a programming language like Python
- C . Understanding the basics of graphic design
- D . Knowledge of ancient history
B
Explanation:
Proficiency in a programming language like Python is a key prerequisite for implementing an HPE machine learning solution.
What is the framework supported by HPE Ezmeral Machine Learning Ops for building machine learning models?
- A . All of the above
- B . PyTorch
- C . Theano
- D . TensorFlow
A
Explanation:
HPE Ezmeral Machine Learning Ops supports frameworks like TensorFlow, PyTorch, and Theano for building machine learning models.
What are the hardware requirements for implementing HPE machine learning solutions?
- A . Any computer with a decent internet connection
- B . Laptops
- C . Smartphones
- D . High-end servers with GPU support
D
Explanation:
High-end servers with GPU support are required for implementing HPE machine learning solutions.
What are some of the current enterprise features offered by HPE in their machine learning solutions?
- A . Automated machine learning model training
- B . Real-time monitoring and predictive maintenance features
- C . Integration with existing IT infrastructure
- D . Advanced analytics capabilities
C
Explanation:
Current enterprise features offered by HPE in their machine learning solutions include integration with existing IT infrastructure, advanced analytics capabilities, automated machine learning model training,
and real-time monitoring and predictive maintenance features.
Which HPE solution helps organizations deploy, manage, and optimize machine learning models at scale?
- A . HPE Ezmeral Data Fabric
- B . HPE Ezmeral ML Ops
- C . HPE Synergy
- D . HPE Ezmeral Container Platform
B
Explanation:
HPE Ezmeral ML Ops helps organizations deploy, manage, and optimize machine learning models at scale.
What is the role of feature selection in machine learning?
- A . To determine the optimal number of features
- B . To select the best machine learning algorithms
- C . To remove irrelevant or redundant features
- D . To evaluate model accuracy
C
Explanation:
Feature selection in machine learning involves selecting the most relevant and important features and removing irrelevant or redundant ones.
Which of the following skills is essential for implementing HPE machine learning solutions?
- A . Public speaking
- B . Critical thinking and problem-solving
- C . Graphic design
- D . Sports
B
Explanation:
Critical thinking and problem-solving skills are essential for implementing HPE machine learning solutions.
When considering the budget for implementing HPE machine learning solutions, why is it important to account for ongoing costs?
- A . To limit the project to a one-time expense
- B . To avoid spending any money on the project
- C . To guarantee immediate ROI
- D . To ensure continuous support and maintenance of the solution
D
Explanation:
When considering the budget for implementing HPE machine learning solutions, it is important to account for ongoing costs to ensure continuous support and maintenance of the solution.