Lectures related to Natural language processing

Delves into coreference resolution, discussing challenges, advancements, and evaluation methods.

Handling Text Data: Document Retrieval and Classification

Covers document retrieval, classification, sentiment analysis, and topic detection using TF-IDF matrices and contextualized word vectors.

Multilingual NLP: Challenges and Innovations

Covers the importance of multilingual NLP and the challenges in scaling language models.

Interpretability & Analysis: Modern NLP

Explores model interpretability in NLP, focusing on probing methods and local explanations to understand model predictions.

NLP Pre-processing: Tokenization, Stop Words, Lemmatization

Covers tokenization, stop words removal, and lemmatization for NLP tasks.

Ethical Considerations in Natural Language Processing

Explores ethical challenges in NLP systems, including biases, toxicity, privacy, and disinformation.

Modern NLP: Introduction

By Antoine Bosselut introduces Natural Language Processing and its challenges, advancements in neural models, and course goals.

Modern NLP: Data Collection, Annotation & Biases

Explores data annotation in NLP and the impact of biases on model fine-tuning.

Natural Language Processing Basics

Covers the basics of Natural Language Processing, including tokenization, part-of-speech tagging, and embeddings, and explores practical applications like sentiment analysis.

Natural Language Generation

Explores Natural Language Generation, covering neural models, biases, ethics, and evaluation challenges.

Word Embeddings: Introduction and Applications

Introduces word embeddings, explaining how they capture word meanings based on context and their applications in natural language processing tasks.

Internship Report: Hangqian Li

Covers an internship report at Tencent Al lab, focusing on 3D avatar reconstruction and neural rendering techniques.

Text Handling: Matrix, Documents, Topics

Explores text handling, focusing on matrices, documents, and topics, including challenges in document classification and advanced models like BERT.

Music Streaming Research: Natural Language Processing at Deezer

Showcases a student's internship at Deezer's research team working on natural language processing.

Learning Policies from Non-Traditional Sources

Explores learning interactive policies from non-traditional sources of data for autonomous systems, including language-informed latent actions and the PLATO framework.

Prompting and Alignment

Explores prompting, alignment, and the capabilities of large language models for natural language processing tasks.

Introduction to Modern Natural Language Processing

Introduces the course on Modern Natural Language Processing, covering its significance, applications, challenges, and advancements in technology.

Neural Word Embeddings

Introduces neural word embeddings and dense vector representations for natural language processing.

Introduction to Natural Language Processing Log in to Mediaspace to watch this video

Introduces the basics of Natural Language Processing, covering challenges, application domains, and linguistic processing levels.

Natural Language Processing: A Primer Log in to Mediaspace to watch this video

Introduces Natural Language Processing (NLP) and its applications, covering tokenization, machine learning, sentiment analysis, and Swiss NLP applications.