Generative AI with Large Language Models Week 3 What projects should one do after completing this course.
Hello @kibrich, welcome to the community!
Here are five project ideas to apply what you’ve learned through hands-on projects:
- Fine-tune a pre-trained model such as GPT or T5 to a specific domain (e.g., legal, medical, or financial). Apply transfer learning techniques to create a domain-specific model that can generate text relevant to that domain. For example, fine-tune a model that can condense long-form content while retaining key information. This is particularly useful for research, legal industries, or corporate reporting. Focus on summarizing long documents such as research papers, legal contracts, or news articles.
- Build a model to generate short stories, poems, or dialogues based on a theme or style. You can also experiment with controlling the generation style by conditioning the output on parameters such as tone or genre.
- Create a task-specific chatbot using generative models. You could focus on making it more personalized by incorporating fine-tuning techniques.
- Develop a project that uses sentiment analysis to guide text generation, such as generating positive or negative product reviews or adjusting marketing content based on customer feedback.
- Create a system that generates personalized product recommendations based on previous purchases or user profiles. Here, an LLM suggests products and explains its recommendations by integrating generative models with recommendation engines.
Hope this helps!