- Presencial
- 14 horas
- Aula Virtual
- No disponible
Generative Pre-trained Transformers (GPT) are state-of-the-art models in natural language processing that have revolutionized various applications, including language generation, text completion, and machine translation. This course provides an in-depth exploration of GPT models, with a focus on GPT-3 and the latest advancements in GPT-4. Participants will gain insights into the architecture, training techniques, and applications of GPT models.
This instructor-led, live training (online or onsite) is aimed at data scientists, machine learning engineers, NLP researchers, and AI enthusiasts who wish to understand the inner workings of GPT models, explore the capabilities of GPT-3 and GPT-4, and learn how to leverage these models for their NLP tasks.
By the end of this training, participants will be able to:
- Understand the key concepts and principles behind Generative Pre-trained Transformers.
- Comprehend the architecture and training process of GPT models.
- Utilize GPT-3 for tasks such as text generation, completion, and translation.
- Explore the latest advancements in GPT-4 and its potential applications.
- Apply GPT models to their own NLP projects and tasks.
Introduction to Generative Pre-trained Transformers (GPT)
- Evolution of language models in NLP
- Introduction to GPT and its significance
- Use cases and applications of GPT models
Understanding GPT Architecture and Training
- Transformer architecture and self-attention mechanism
- Pre-training and fine-tuning of GPT models
- Transfer learning and domain adaptation with GPT
Exploring GPT-3
- Overview of GPT-3 architecture and features
- Understanding the model's capabilities and limitations
- Hands-on exercises with GPT-3 for text generation and completion
Recent Advancements: GPT-4
- Overview of the latest GPT-4 model
- Key enhancements and improvements over previous versions
- Exploring the expanded capabilities of GPT-4
Applications of GPT Models
- Text generation and completion using GPT models
- Machine translation with GPT
- Dialogue systems and chatbots with GPT
- Creative writing and storytelling using GPT models
Fine-tuning GPT Models
- Techniques for fine-tuning GPT models on specific tasks
- Adapting GPT for domain-specific applications
- Best practices for fine-tuning and model evaluation
Ethical Considerations and Challenges
- Ethical implications of using large language models
- Bias and fairness issues in GPT models
- Mitigating risks and ensuring responsible use of GPT models
Future Trends and Beyond GPT-4
- Emerging trends in NLP and generative models
- Research frontiers and potential advancements beyond GPT-4
Summary and Next Steps
- Recap of key learnings and takeaways from the course
- Resources for further exploration and learning opportunities in GPT models and NLP
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