Natural language

Related lectures (32)

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Explores deep learning for question answering, analyzing neural networks and model robustness to noise.

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

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

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

Covers keyphrase extraction, a method to extract important phrases from text for document summarization, indexing, and search.

Introduces financial markets, time series, machine learning applications in finance, and natural language processing.

Explores the evolution from sparse modeling to sparse communication in neural networks for natural language processing tasks.

Examines systematicity, compositionality, neural network challenges, and unsupervised learning in NLP.

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

Covers the fundamentals of deep learning, including data, architecture, and ethical considerations in model deployment.