Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to Pre-trained Models
- Defining pre-trained models
- Advantages of utilizing pre-trained models
- A look at popular pre-trained models (e.g., BERT, ResNet)
Delving into Pre-trained Model Architectures
- Foundations of model architecture
- Concepts of transfer learning and fine-tuning
- The process of building and training pre-trained models
Environment Configuration
- Installation and setup of Python and essential libraries
- Navigating pre-trained model repositories (e.g., Hugging Face)
- Loading and testing pre-trained models
Practical Application of Pre-trained Models
- Leveraging pre-trained models for text classification
- Using pre-trained models for image recognition
- Fine-tuning models for custom datasets
Deployment of Pre-trained Models
- Exporting and storing fine-tuned models
- Integrating models into software applications
- Foundations of deploying models in production environments
Challenges and Best Practices
- Recognizing model limitations
- Preventing overfitting during the fine-tuning process
- Promoting ethical AI model usage
Emerging Trends in Pre-trained Models
- New architectures and their potential applications
- Progress in transfer learning
- Exploration of large language models and multimodal models
Overview and Future Directions
Requirements
- A foundational grasp of machine learning principles
- Proficiency in Python programming
- Basic competence in data management using libraries such as Pandas
Target Audience
- Data scientists
- AI enthusiasts
Testimonials (2)
Getting people that never used AI some repetition in prompting and people that do use AI to consider different methods to using it.
Matthew Gay - Tarsus Pharmaceuticals
Course - Artificial Intelligence (AI) Overview
Working from first principles in a focused way, and moving to applying case studies within the same day
