Tutorial 6 - Transfer learning & Domain adaptation | Deep Learning on Computational Accelerators

Tutorial 7 - Deep reinforcement learning | Deep Learning on Computational Accelerators

[ML 2021 (English version)] Lecture 27: Domain Adaptation

Tutorial 6 - Transfer Learning & Domain Adaptation | Deep Learning on Computational Accelerators

Transfer learning and Transformer models (ML Tech Talks)

Визуализация скрытого пространства: PCA, t-SNE, UMAP | Глубокое обучение с анимацией

Управление поведением LLM без тонкой настройки

Shen Liang - Deep Domain Adaptation and Generalization + Hands-On Workshop

CS480/680 Lecture 19: Attention and Transformer Networks

Lecture 1 - Introduction | Deep Learning on Computational Accelerators

Lecture 16 | Adversarial Examples and Adversarial Training

Новогодний разворот! Встречаем 2026 с Алексеем Венедиктовым*, Алексеем Ракшой* и Игорем Липсицем*

Stanford CS330 Deep Multi-Task & Meta Learning - Domain Adaptation l 2022 I Lecture 13

Создание нейронной сети С НУЛЯ (без Tensorflow/Pytorch, только NumPy и математика)

Почему «Трансформеры» заменяют CNN?

An Introduction to Graph Neural Networks: Models and Applications

Transformers in Vision: From Zero to Hero

OpenAI CLIP: Соединение текста и изображений (объяснение в статье)

From Deep Learning of Disentangled Representations to Higher-level Cognition

Ian Goodfellow: Adversarial Machine Learning (ICLR 2019 invited talk)

Supervised and self-supervised transfer learning (with PyTorch Lightning)