Transformer: Pre-Training

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (31)

Page 2 of 4

Explores pretraining models like BERT, T5, and GPT, discussing their training objectives and applications in natural language processing.

Neural Machine Translation

Explores the evolution and challenges of Neural Machine Translation systems and the evaluation metrics used in this field.

Machine Translation: Sequence-to-Sequence and Attention

Explores the advancements in Machine Translation, focusing on Sequence-to-Sequence models and Attention mechanisms.

Deep Learning for NLP

Explores deep learning for NLP, covering word embeddings, context representations, learning techniques, and challenges like vanishing gradients and ethical considerations.

Pre-Training: BiLSTM and Transformer

Delves into pre-training BiLSTM and Transformer models for NLP tasks, showcasing their effectiveness and applications.

Contextual Representations: ELMO and BERT Overview

Covers contextual representations in NLP, focusing on ELMO and BERT architectures and their applications in various tasks.

Transformers: Overview and Self-Attention

Provides an overview of Transformers, self-attention, multi-headed attention, and the Transformer decoder and encoder.

BERT: Pretraining and Applications

Delves into BERT pretraining for transformers, discussing its applications in NLP tasks.

Transformers in Vision: Applications and Architectures

Covers the impact of transformers in computer vision, discussing their architecture, applications, and advancements in various tasks.

Modern NLP and Ethics in NLP

Delves into advancements and challenges in NLP, along with ethical considerations and potential harms.