Techniques For Reducing Model Hallucinations | Model Fine-tuning | Beginner Friendly Approach скачать в хорошем качестве

Techniques For Reducing Model Hallucinations | Model Fine-tuning | Beginner Friendly Approach

Learn different techniques you can apply to reduce LLM hallucination. From prompt engineering to Retrieval Augemented Generation (RAG) to fine-tuning. What you'll learn: Introduction to model fine-tuning Understanding RAG systems Advantages and disadvantages of each Real-world use cases How to choose the right approach Combining both techniques Perfect for beginners getting started with AI model customization. Subscribe for more beginner-friendly AI tutorials. Tags: #ModelFineTuning #RAG #AI #MachineLearning #LLM #BeginnerTutorial #ArtificialIntelligence #DataScience #Programming #TechEducation #promptengineering #prompting Buy me a coffee: https://www.buymeacoffee.com/princez3 Follow me on social media: Discord community server:   / discord   twitter:   / prince_krampah   Channel main page:    / codewithprince   Hope you enjoy today's video. Please show your love and support by just liking and subscribing to the channel so we can grow a strong and powerful community. Activate the 🔔 beside the subscribe button to get the notification!📩 If you have any questions or requests feel free to leave them in the comments below. Thank you for watching and see you in the next video!! This video covers techniques to reduce ai hallucination in large language models, including prompt engineering and retrieval augmented generation. Learn simple examples and clear visuals to make AI answers more accurate. We will also discuss how fine tuning llm can improve results.