HP HPE2-T38 HPE AI and Machine Learning Online Training
HP HPE2-T38 Online Training
The questions for HPE2-T38 were last updated at Feb 20,2025.
- Exam Code: HPE2-T38
- Exam Name: HPE AI and Machine Learning
- Certification Provider: HP
- Latest update: Feb 20,2025
Which aspect of HPE’s machine learning solutions can help businesses in developing a better understanding of customer needs and preferences?
- A . Integration with CRM systems
- B . Algorithm transparency
- C . Automated model training
- D . Real-time data processing
How can HPE ML solutions contribute to revenue growth for businesses?
- A . Predicting customer churn
- B . Recommending cross-sell opportunities
- C . Identifying upsell opportunities
- D . All of the above
Which of the following is NOT a type of machine learning algorithm?
- A . Supervised learning
- B . Reinforcement learning
- C . Pre-defined learning
- D . Unsupervised learning
What deployment options are available for models created using the HPE Machine Learning [PDK]?
- A . Cloud deployment only
- B . Hybrid deployment (on-premises and cloud)
- C . On-premises deployment only
- D . No deployment options are available
In what way can HPE ML solutions help businesses in terms of competitive advantage?
- A . Providing real-time insights
- B . Improving customer retention
- C . Enhancing product development
- D . All of the above
What is a key prerequisite for implementing HPE machine learning solutions?
- A . Understanding of data pre-processing techniques
- B . Experience in neural networks
- C . Basic knowledge of Python programming language
- D . High-speed internet connection
Why is domain expertise considered a prerequisite for effectively deploying HPE machine learning solutions?
- A . It speeds up training time
- B . It helps in understanding the nuances of the business problem
- C . It reduces the need for model evaluation
- D . It eliminates the need for data preprocessing
What is an essential requirement for ensuring model interpretability in HPE machine learning solutions?
- A . Explainable AI techniques
- B . Biometric authentication
- C . Real-time prediction capabilities
- D . Black-box algorithms
How does regulatory compliance influence the requirements for deploying HPE machine learning solutions?
- A . It eliminates the need for model explainability
- B . It increases the need for data privacy measures
- C . It reduces the need for high-quality data sources
- D . It simplifies model evaluation processes
What is a key feature of the HPE Machine Learning [PDK] for model training?
- A . Real-time data visualization
- B . Email notifications for model status
- C . Automated hyperparameter tuning
- D . Cloud-based data storage
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