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Understanding functional and technical aspects of Overview of TensorFlow, programming basics, and methods of using TensorFlow programming for image recognition, speech recognition, and human-machine dialogue
The following will be discussed in HUAWEI H13-311 exam dumps:
- Enactment Functions
- Normal Machine Learning Algorithms
- Enhancer
- Outline of Deep Learning
- Sorts of Neural Networks
- Hyperparameter and Validation Set
- Uses of Deep Learning
- Regularization in Deep Learning
- Most extreme Likelihood Estimation
- Boundary Estimation
- Propaedeutics of Deep Learning
- Bayes Estimation
- Learning Algorithms
- Definition and Development of Neural Networks
- Perceptron and Training Rules
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Understanding functional and technical aspects of Overview of Deep Learning
The following will be discussed in HUAWEI H13-311 exam dumps:
- Utilizing the Model
- TensorFlow Development Environment Setup
- TensorFlow Basics
- TensorFlow Characteristics
- Characterizing the Operation
- TensorFlow Modules
- TensorFlow Overview
- Instating All Variables
- Characterizing the TensorFlow Input Node
- Upgrading Functions and Objectives
- Characterizing the Learning Parameter Variable
- Testing the Model
- Fundamental Development Steps Using TensorFlow
- Repeat and Update Parameters to the Optimal Solution
Understanding functional and technical aspects of Python programming basics
The following will be discussed in HUAWEI H13-311 exam dumps:
- Prologue to Python
- Restrictive and Loop Statements
- Records and Tuples
- Customary Expressions
- Date and Time
- Record Manipulation
- Strings
- Word references
- Capacities
- Article Oriented Programming
Huawei H13-311-ENU Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Machine Learning Basics | - Supervised learning
|
| Artificial Intelligence Fundamentals | - AI concepts and basic principles
|
| AI Development and Huawei AI Ecosystem | - Huawei AI platform and tools
|
| Deep Learning Fundamentals | - Common deep learning models
|
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