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Understanding functional and technical aspects of Essential mathematics knowledge and pre-knowledge for Deep Learning
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- Minor Probability
- Linear Algebra
- Ceaseless Variable
- Restrictive Probability
- Irregular Variables
- Sick Condition
- Numeric Calculation
- Uncommon Matrices
- Likelihood Distribution
- Particular Value Decomposition
- Eigendecomposition
- Moore-Penrose Pseudoinverse
- Determinants
- Organized Statistical Model
- Basic Probability Distribution
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- Follow Operator
- Likelihood Theory and Information Theory
- Freedom and Conditional Independence
- Model: Principal Component Analysis
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Understanding functional and technical aspects of Overview of Deep Learning
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- TensorFlow Development Environment Setup
- Utilizing the Model
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- TensorFlow Modules
- Instating All Variables
- TensorFlow Characteristics
- Upgrading Functions and Objectives
- Repeat and Update Parameters to the Optimal Solution
- Characterizing the Learning Parameter Variable
- TensorFlow Overview
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- Characterizing the Operation
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Topics of Huawei Certified ICT Associate-Artificial Intelligence
The following will be discussed in HUAWEI H13-311 practice exam and HUAWEI H13-311 practice exams:
- Outline of TensorFlow, programming nuts and bolts, and techniques for utilizing TensorFlow programming for picture acknowledgment, discourse acknowledgment, and human-machine exchange
- Fundamental science information and pre-information for Deep Learning
- Python programming nuts and bolts
- Outline of Huawei cloud EI
- Outline of computerized reasoning
- Outline of Deep Learning
