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Related lectures (32)

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Handling Text Data: Document Retrieval and Classification

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

Document Retrieval and Classification

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

Introduction to Natural Language Processing

Covers the basics of Natural Language Processing, from traditional to modern approaches, highlighting the challenges and importance of studying both methods.

Ethics in NLP

Discusses the ethical implications of NLP systems, focusing on biases, toxicity, and privacy concerns in language models.

Modern NLP: Introduction

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

Music Streaming Research: Natural Language Processing at Deezer

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

Modern NLP: Data Collection, Annotation & Biases

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

Machine Translation: Attention Mechanism

Explores the attention mechanism in machine translation, addressing the bottleneck problem and improving NMT performance significantly.

Internship Report: Hangqian Li

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

Ethical Considerations in Natural Language Processing

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