Lecture

Language Modelling and Recurrent Neural Networks

Related lectures (79)
Modern Natural Language Processing: Core Methods and Applications
Delves into core methods and applications of modern natural language processing, addressing challenges and advancements.
Prompting and Alignment
Explores prompting, alignment, and the capabilities of large language models for natural language processing tasks.
Batch Normalization: Why It Works
Explores the aim and process of batch normalization in deep neural networks, emphasizing its importance in stabilizing mean input and solving the vanishing gradient problem.
Transformer: Pre-Training
Explores the Transformer model, from recurrent models to attention-based NLP, highlighting its key components and significant results in machine translation and document generation.
Natural Language Generation
Explores Natural Language Generation, covering neural models, biases, ethics, and evaluation challenges.
Biological structure and function emerge from unsupervised learning
Delves into how biological structure and function are decoded through unsupervised learning of protein sequences.
Theoretical Properties of RNNs
Explores the theoretical properties and practical power of Recurrent Neural Networks, including their relationship to state machines and Turing completeness.
Introduction to Reinforcement Learning: Concepts and Applications
Introduces reinforcement learning, covering its concepts, applications, and key algorithms.
BERT: Pretraining and Applications
Delves into BERT pretraining for transformers, discussing its applications in NLP tasks.
Question Answering: Deep Learning Insights
Explores question answering systems, reading comprehension models, and the challenges in achieving accurate responses.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.