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Related lectures (32)
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Coreference Resolution
Covers coreference resolution, models, applications, challenges, and advancements in natural language processing.
Modern NLP: Introduction
By Antoine Bosselut introduces Natural Language Processing and its challenges, advancements in neural models, and course goals.
Sequence to Sequence Models: Overview and Applications
Covers sequence to sequence models, their architecture, applications, and the role of attention mechanisms in improving performance.
Non conceptual knowledge systems
Explores the impact of Deep learning on Digital Humanities, focusing on non conceptual knowledge systems and recent advancements in AI.
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.
Memory-Efficient Adaptive Optimization
Explores memory-efficient adaptive optimization for large-scale learning and the challenges of memory overhead in training large models.
Transformers: Revolutionizing Attention Mechanisms in NLP
Covers the development of transformers and their impact on attention mechanisms in NLP.
Charged Particle in Magnetic Field: Landau Levels
Explores charged particles in a magnetic field, focusing on Landau levels and translation generators.
Transformers: Pretraining and Decoding Techniques
Covers advanced transformer concepts, focusing on pretraining and decoding techniques in NLP.
Automatic Synthesis of OS Code
Covers the automatic synthesis of OS code to ease the burden of developers in configuring translation hardware.