Overview
Fine tuning is a process in machine learning where we take a pre-trained model and adjust it to perform better on a specific task. This helps the model learn from new data while retaining its previous knowledge. In this introduction, you will discover the basics of fine tuning and how it can improve the performance of generative AI applications.
📚 Key Learning Objectives
- ✓ Define fine tuning in the context of machine learning.
- ✓ Identify the benefits of fine tuning pre-trained models.
- ✓ Explain the steps involved in the fine tuning process.
- ✓ Apply fine tuning techniques to a sample dataset.
- ✓ Evaluate the performance of a fine-tuned model.
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