NLP Training Lab
Introduction
The Natural Language Processing (NLP) Lab covers typical NLP application scenarios and provides detailed training processes, including data annotation, model training, model call and deployment, to help students quickly get started and master relevant knowledge and skills.
Enterprise Positions: Data Collection and Annotation Engineer, Artificial Intelligence Training Engineer, Artificial Intelligence Application Development Engineer
Applicable Majors: Artificial Intelligence Engineering Technology/Computer-related Majors
Course Products: professional core course and professional extension course in natural language processing
Project Products: multiple projects aimed at natural language processing and centered around techniques such as text preprocessing, feature extraction, text classification, semantic analysis
Intelligent Hardware: Touch Screen, Edge Processor, etc.
Applicable Scenes: Professional Teaching, Integrated Training, Competition Training
Feature
Integration of Theory and Practice
Comprehensive Technological Coverage
The lab covers typical application scenarios of NLP and provides detailed training processes, including data annotation, model training, model call and deployment, to help students quickly get started and master relevant knowledge and skills.
The Natural Language Processing (NLP) Lab covers typical NLP application scenarios and provides detailed training processes, including data annotation, model training, model call and deployment, to help students quickly get started and master relevant knowledge and skills.
Enterprise Positions: Data Collection and Annotation Engineer, Artificial Intelligence Training Engineer, Artificial Intelligence Application Development Engineer
Applicable Majors: Artificial Intelligence Engineering Technology/Computer-related Majors
Course Products: professional core course and professional extension course in natural language processing
Project Products: multiple projects aimed at natural language processing and centered around techniques such as text preprocessing, feature extraction, text classification, semantic analysis
Intelligent Hardware: Touch Screen, Edge Processor, etc.
Applicable Scenes: Professional Teaching, Integrated Training, Competition Training
Feature
Integration of Theory and Practice
- With a complete and proven course resource
- Including various granularity of experimental resources
- Including real-world training project resources from enterprises
Comprehensive Technological Coverage
The lab covers typical application scenarios of NLP and provides detailed training processes, including data annotation, model training, model call and deployment, to help students quickly get started and master relevant knowledge and skills.
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