Tutorial 125 - Using pretrained deep learning model as feature extractor for XGBoost segmentation

Tutorial 124 - Using pretrained models as encoders in U-Net

Tutorial 126 - Using pretrained deep learning model as feature extractor for XGBoost classification

158b - Transfer learning using CNN (VGG16) as feature extractor and Random Forest classifier

Управление поведением LLM без тонкой настройки

Прогнозирование временных рядов с помощью XGBoost — используйте Python и машинное обучение для пр...

Tutorial 123 - Deep learning architectures and benefits via transfer learning

195 - Image classification using XGBoost and VGG16 imagenet as feature extractor

Tutorial 122 - Segmenting 3D datasets using 3D U-Net

Цепи Маркова — математика предсказаний [Veritasium]

Tutorial 83 - Image classification using traditional machine learning

Подробное объяснение тонкой настройки LoRA и QLoRA

Tutorial 74 - What are Gabor filters and how to use them to generate features for machine learning?

Трёхмерные сверточные сети | Лекция 41 (часть 2) | Прикладное глубокое обучение

A Good Feature Extractor Is All You Need in Histopathology: Georg Wölflein, 05/02/24

RAG простыми словами: как научить LLM работать с файлами

Tutorial 120 - Applying trained U-Net model to segment large images

159 - Convolutional filters + Random Forest for image segmentation.

Автоэнкодеры | Глубокое обучение в анимации

XGBoost in Python from Start to Finish

Extract Features from Image using Pretrained Model | Python