Understanding functional and technical aspects of Overview of Deep Learning
The following will be discussed in HUAWEI H13-311 exam dumps:
- TensorFlow Basics
- Characterizing the Operation
- TensorFlow Overview
- TensorFlow Characteristics
- Characterizing the TensorFlow Input Node
- Characterizing the Learning Parameter Variable
- TensorFlow Modules
- Utilizing the Model
- Upgrading Functions and Objectives
- Repeat and Update Parameters to the Optimal Solution
- Fundamental Development Steps Using TensorFlow
- TensorFlow Development Environment Setup
- Testing the Model
- Instating All Variables
Who should take the Huawei Certified ICT Associate-Artificial Intelligence
Engineers who need to master AI technologies, learn and use deep learning algorithms, and master Huawei AI-related product technologies.
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Huawei H13-311-ENU Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Machine Learning Overview | 20% | - Basic concepts and classification - Common algorithms and models - Model training and evaluation |
| Huawei AI Platform & Applications | 8% | - Typical AI application scenarios - Huawei Cloud EI and ModelArts - Ascend computing platform and Atlas series |
| AI Development Frameworks | 12% | - Huawei MindSpore framework introduction - TensorFlow basics and usage |
| Deep Learning Overview | 25% | - Neural network fundamentals - Training mechanisms and optimization - CNN, RNN and basic architectures |
| Artificial Intelligence Overview | 15% | - Huawei AI strategy and full-stack architecture - History and development of AI - AI technology and application fields |
| Mathematics and Python Basics | 20% | - Python programming fundamentals - Data processing and visualization - Linear algebra, probability and statistics |
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