This page was exported from Actual Test Materials [ http://blog.actualtests4sure.com ] Export date:Sun Mar 9 14:23:18 2025 / +0000 GMT ___________________________________________________ Title: [Q202-Q216] 2025 Updated H13-311_V3.5 Tests Engine pdf - All Free Dumps Guaranteed! --------------------------------------------------- 2025 Updated H13-311_V3.5 Tests Engine pdf - All Free Dumps Guaranteed! Latest HCIA-AI H13-311_V3.5 Actual Free Exam Questions Huawei H13-311_V3.5 (HCIA-AI V3.5) Certification Exam is a highly sought-after certification for IT professionals looking to enhance their skills in the field of artificial intelligence. HCIA-AI V3.5 certification exam is designed to assess the candidate's knowledge and skills in AI, machine learning, and deep learning using the Huawei framework. With this certification, IT professionals can demonstrate their proficiency in designing and implementing AI solutions, making them a valuable asset to any organization.   Q202. On-Device Execution, that is, the entire image is offloaded and executed, and the computing power of the Yiteng chip can be fully utilized, which can greatly reduce the interaction overhead, thereby increasing the accelerator occupancy rate.On-Device The following description is wrong?  MindSpore Realize decentralized autonomy through adaptive graph optimization driven by gradient data A11 Reduce, Gradient aggregation is in step, and calculation and communication are fully streamlined  Challenges of model execution under super chip computing power: Memory wall problems, high interaction overhead, and difficulty in data supply. Partly in Host Executed, partly in Device Execution, interaction overhead is even much greater than execution overhead, resulting in low accelerator occupancy  MindSpore Through the chip-oriented depth map optimization technology, the synchronization wait is less, and the “data computing communication” is maximized. The parallelism of “trust”, compared with training performance Host Side view scheduling method is flat  The challenge of distributed gradient aggregation under super chip computing power:ReslNet50 Single iteration 20ms Time will be generated The synchronization overhead of heart control and the communication overhead of frequent synchronization. Traditional methods require 3 Synchronization completed A11 Reduce, Data-driven method autonomy A11 Reduce, No control overhead Q203. Regarding the convolutional neural network pooling layer, the following description is correct?  Pooling operation is realized by scanning window  The pooling layer can play a role in dimensionality reduction  Commonly used pooling methods include maximum pooling and average pooling  The pooled feature image becomes smaller Q204. Which of the following does the convolutional neural network structure not include?  Convolutional layer  Pooling layer  Loop layer  Fully connected layer Q205. Which of the following are the characteristics of the Python language? {Multiple choice)  Explanatory  Process oriented  Object-oriented  Dynamic data type Q206. Regularization is an important and effective technique for reducing generalization errors in traditional machine learning. The following techniques are regular.The technology is:  L1 Regularization  L2 Regularization  Dropout  Momentum optimizer Q207. Google proposed the concept of knowledge graph and took the lead in applying knowledge graphs to search engines in 2012, successfully improving users’ search quality and experience.  TRUE  FALSE Google introduced the concept of the knowledge graph in 2012, and it played a significant role in improving the search engine’s ability to understand the relationships between different entities (e.g., people, places, things). This allowed Google to provide richer, more relevant search results by moving from keyword-based search to a more semantic understanding of the user’s query. The knowledge graph helps organize information in a more structured way, making it easier for users to find relevant answers quickly and enhancing the overall search experience.HCIA AIReference:AI Overview: Discusses the impact of knowledge graphs on search engines and their importance in improving AI-driven user experiences.Cutting-edge AI Applications: Provides insights into how knowledge graphs are applied in AI systems for improving information retrieval.Q208. TensorFlow is Google’s first generation of proprietary machine learning systems  True  False Q209. The matrix produced by the exchange of matrix A rows and columns is called the transpose of A.What are the correct properties of matrix transposition? (Multiple Choice)  (A T ) T = A  (A+ 8) T = AT +BT  (!EA) T = !EAT  (AB} T = A T +BT Q210. In the deep learning network, the backpropagation algorithm is used to find the optimal parameters. What rules are used in the backpropagation algorithm to obtain the derivation layer by layer?  Chain rule  Cumulative rule  Law of reciprocity  Rule of Normalization Q211. In deep learning tasks, when encountering data imbalance problems, which of the following methods can we use to solve the problem?  batch deletion  Random oversampling  Synthetic sampling  Random undersampling Q212. Recurrent neural networks can capture dynamic information in serialized data.  TRUE  FALSE Q213. PyTorch All existing versions support Python2 with Python3?  TRUE  FALSE Q214. In MindSpore, mindspore.nn.Conv2d() is used to create a convolutional layer. Which of the following values can be passed to this API’s “pad_mode” parameter?  pad  same  valid  nopadding The pad_mode parameter in mindspore.nn.Conv2d() can take values such as:same: Ensures the output has the same spatial dimensions as the input.valid: Performs convolution without padding, resulting in an output smaller than the input.Other values like “pad” and “nopadding” are not valid options for the pad_mode parameter.Q215. In polynomial regression, there is a square term in the formula of the model, so it is not linear.  TRUE  FALSE Q216. The loss function reflects the error between the target output and actual output of the neural network.The commonly used loss function in deep learning is:  Exponential loss function  Mean square loss function  Log loss function  Hinge Loss function  Loading … To obtain the Huawei H13-311_V3.5 examination, the interested candidates need to have a basic knowledge of AI, data science concepts, and Python programming languages. Individuals who wish to attempt H13-311_V3.5 exam are advised to devote adequate time to preparation and get themselves familiarized with the exam format. Practice tests and sample papers online are also helpful resources for those who want to pass the exam with flying colors.   H13-311_V3.5 Dumps Updated Practice Test and 430 unique questions: https://www.actualtests4sure.com/H13-311_V3.5-test-questions.html --------------------------------------------------- Images: https://blog.actualtests4sure.com/wp-content/plugins/watu/loading.gif https://blog.actualtests4sure.com/wp-content/plugins/watu/loading.gif --------------------------------------------------- --------------------------------------------------- Post date: 2025-03-02 13:27:30 Post date GMT: 2025-03-02 13:27:30 Post modified date: 2025-03-02 13:27:30 Post modified date GMT: 2025-03-02 13:27:30