Transfer Learning

Understands the concept of transfer learning: pre-trained models, feature extraction, fine-tuning. Applies transfer learning via Hugging Face and torchvision for image and text tasks. Knows when transfer learning is more effective than training from scratch.

Knows transfer learning basics: pre-training, fine-tuning, feature extraction. Understands how pre-trained LLMs are used for downstream tasks and applies basic transfer learning approach.

Applies transfer learning with pre-trained models (ResNet, BERT) for domain-specific tasks. Fine-tunes models on custom datasets with appropriate learning rate scheduling. Evaluates trade-offs between full fine-tuning and feature extraction.

Applies transfer learning techniques for LLM adaptation: LoRA, QLoRA, and prompt tuning. Fine-tunes foundation models on domain-specific corpora. Evaluates catastrophic forgetting and optimizes training efficiency.

Designs transfer learning pipelines for scalable fine-tuning. Applies multi-task transfer learning, domain adaptation, few-shot learning. Creates domain-specific pre-trained models for the organization. Optimizes compute cost of transfer learning.

Designs advanced transfer learning strategies: continual pre-training, multi-task transfer, cross-lingual transfer. Optimizes the trade-off between forgetting and adaptation for domain-specific models.

Defines transfer learning strategy for the data science team. Establishes internal model hub with pre-validated pre-trained models. Coordinates shared pre-training efforts and knowledge transfer across projects.

Defines transfer learning standards for the LLM team. Establishes guidelines for base model selection, transfer strategy, evaluation. Coordinates transfer learning experiments and model selection.

Shapes pre-trained models and transfer learning strategy at organizational level. Defines investments in pre-training infrastructure. Evaluates foundation models and their applicability for organizational tasks.

Shapes enterprise transfer learning strategy. Defines approaches to foundation model selection, org-wide transfer practices, and knowledge sharing between teams and products.