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Course Outline
Introduction to Qwen for NLP
- Overview of Qwen's architecture and capabilities
- Setting up the environment and accessing Qwen API
- Key features and NLP-focused functionalities
Advanced Text Processing with Qwen
- Text generation and language modeling
- Sentiment analysis and emotion detection
- Summarization and paraphrasing
- Entity recognition and text classification
Integrating Qwen into NLP Workflows
- APIs and libraries for seamless integration
- Building pipelines for text preprocessing and analysis
- Deploying Qwen models in production environments
Customization and Fine-Tuning
- Adapting Qwen to specific NLP tasks
- Training custom models with domain-specific data
- Techniques for improving model performance
Evaluation and Performance Optimization
- Metrics for assessing NLP model quality
- Evaluating Qwen’s output and error analysis
- Optimizing computational efficiency
Case Studies and Best Practices
- Applications of Qwen in industry-specific NLP tasks
- Best practices for large-scale deployment
- Addressing challenges and limitations of Qwen
Summary and Next Steps
Requirements
- Advanced knowledge of natural language processing (NLP)
- Experience with AI model development
- Proficiency in Python programming
Audience
- NLP specialists
- Data scientists
- AI researchers
14 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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