HPE AI and Machine Learning HPE2-T38 Dumps Questions

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

Answer: A Explanation: Explainable AI techniques are an essential requirement for ensuring model interpretability in HPE machine learning solutions.

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

Answer: A Explanation: Integration with CRM systems is a key feature of HPE's machine learning solutions that can help businesses understand customer needs and preferences.

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

Answer: B Explanation: Domain expertise is considered a prerequisite for effectively deploying HPE machine learning solutions as it helps in understanding the nuances of the business problem.

Which HPE offering provides a scalable distributed machine learning platform for enterprise AI and ML workloads? A. HPE Ezmeral Container Platform B. HPE Ezmeral Machine Learning Ops C. HPE Ezmeral Data Fabric D. HPE Ezmeral ML Ops

Answer: B Explanation: HPE Ezmeral Machine Learning Ops provides a scalable distributed machine learning platform for enterprise AI and ML workloads.

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

Answer: B Explanation: Models created using the HPE Machine Learning [PDK] can be deployed in a hybrid manner, supporting both on-premises and cloud deployment options.

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

Answer: B Explanation: Regulatory compliance influences the requirements for deploying HPE machine learning solutions by increasing the need for data privacy measures.

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

Answer: C Explanation: A key feature of the HPE Machine Learning [PDK] for model training is automated hyperparameter tuning to optimize model performance.

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

Answer: C Explanation: Having a basic knowledge of the Python programming language is a key prerequisite for implementing HPE machine learning solutions.

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

Answer: D Explanation: HPE ML solutions can help businesses gain a competitive advantage by providing real-time insights, enhancing product development, and improving customer retention.

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

Answer: C Explanation: Pre-defined learning is not a type of machine learning algorithm.

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

Answer: D Explanation: HPE ML solutions can contribute to revenue growth for businesses by identifying upsell opportunities, recommending cross-sell opportunities, and predicting customer churn.

How can HPE ML solutions help businesses in terms of customer engagement and satisfaction? A. Personalizing marketing campaigns B. Recommending products or services C. Predicting customer behavior D. All of the above

Answer: D Explanation: HPE ML solutions can help businesses enhance customer engagement and satisfaction by personalizing marketing campaigns, predicting customer behavior, and recommending products or services.

https://www.certspots.com/exam/hpe2-t38/

we do provide effective HPE2-T38 practice exam questions that provide you with skills validated by the exam.