Curated collection of courses, tutorials, libraries, and research papers
Comprehensive 4-course series covering NLP fundamentals, sequence models, attention mechanisms, and transformers. Taught by industry experts.
Visit Course →Stanford's renowned NLP course covering neural networks, word vectors, transformers, and modern NLP applications. Includes lecture videos and assignments.
Visit Course →Learn how to use the Transformers library and work with models like BERT, GPT, and T5. Includes hands-on exercises and real-world projects.
Visit Course →Practical deep learning for NLP with a focus on getting results quickly. Learn by building real applications using PyTorch and modern architectures.
Visit Course →Essential papers that shaped modern NLP
Vaswani et al. - Introduced the Transformer architecture
Read Paper →Devlin et al. - Revolutionized transfer learning in NLP
Read Paper →Brown et al. - Introduced GPT-3 and in-context learning
Read Paper →Peters et al. - Context-dependent word embeddings
Read Paper →Sutskever et al. - Foundation of neural machine translation
Read Paper →Active community discussing NLP research and applications
Get help with Transformers and NLP models
Q&A for NLP programming questions
Deep dives into NLP research and techniques
Visual explanations of NLP concepts
In-depth ML and NLP tutorials
Explore datasets and put your knowledge into practice
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