Fine-tuning

Fine-tuning is a crucial technique in deep learning that allows for the adaptation of pre-trained models to specific tasks or datasets. Coursera's Fine-tuning catalogue teaches you how to leverage transfer learning principles to efficiently repurpose existing neural networks for new applications, significantly reducing training time and computational resources. You'll learn to modify model architectures, freeze and unfreeze layers strategically, and implement fine-tuning techniques using popular frameworks like PyTorch and TorchVision. This skill empowers data scientists and machine learning engineers to create high-performing models for various domains, including computer vision and natural language processing, even with limited data or computational constraints.

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Results for "Fine-tuning"

  • Skills you'll gain: Fine-tuning, Generative AI, Reinforcement Learning, Large Language Modeling, Generative Model Architectures, Machine Learning Methods, Model Optimization, Model Training, Model Evaluation

  • Skills you'll gain: Fine-tuning, Model Optimization, Model Training, Generative AI, Model Evaluation, Large Language Modeling, Version Control, Performance Tuning, Development Environment, Data Preprocessing, Natural Language Processing, Linear Algebra

  • Alberta Machine Intelligence Institute

    From the course: Building and Deploying Generative AI Models·Lesson: RAG vs. Finetuning

  • From the course: From Recipe to Chef - Become an LLM Engineer·Lesson: Fine-Tuning – Customizing the Recipe

  • From the course: Building Intelligent Troubleshooting Agents·Lesson: Module summary: LLM fine-tuning for task-specific adaptation

  • From the course: AI Image Generation in Python: Stable Diffusion & LoRA·Lesson: Comparison & Ranking Charts

  • From the course: Advanced Data Analysis with Generative AI·Lesson: Fine Tuning GenAI models for specific NLP tasks

  • From the course: Advanced Data Analysis with Generative AI·Lesson: Fine Tuning GenAI models for specific NLP tasks

  • From the course: Transformers in Action: A Practical Approach to NLP and AI·Lesson: Fine-Tuning Basics

  • From the course: Generative AI: Fine-Tuning LLMs and Diffusion Models·Lesson: Introduction to PEFT & Low-Rank Adaptation

  • From the course: AI Systems Design: RAG Pipelines and LLM Architecture·Lesson: RAG vs Fine-Tuning

  • From the course: Generative AI Fundamentals for Beginners·Lesson: AI Training and Fine-Tuning