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Huawei H13-331_V1.0 Exam Syllabus Topics:

SectionObjectives
Topic 1: Model Training and Optimization- Training process
  • 1. Loss functions and optimizers
    • 2. Forward and backward propagation
      - Optimization techniques
      • 1. Overfitting prevention methods
        • 2. Learning rate scheduling
          Topic 2: Artificial Intelligence Fundamentals- Machine Learning Basics
          • 1. Model training workflow
            • 2. Supervised vs unsupervised learning concepts
              - Deep Learning Fundamentals
              • 1. Common activation functions
                • 2. Neural network structure
                  Topic 3: MindSpore Framework Basics- Programming model
                  • 1. Model definition and training process
                    • 2. Dataset and data pipeline
                      - MindSpore architecture
                      • 1. Computational graph execution modes
                        • 2. Core components of MindSpore
                          Topic 4: AI Model Deployment and Acceleration- Model inference
                          • 1. Inference pipeline
                            • 2. Model export and conversion
                              - Hardware acceleration
                              • 1. Performance optimization strategies
                                • 2. Ascend AI processor usage

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