NLP - gusenov/kb GitHub Wiki
History
- Language Models were invented over 110+ years ago by Andrey Markov of the Markov probability and Markov chains fame
- IEEE Spectrum
- history of natural language processing
- Natural Language Processing Dates Back to Kabbalist Mystics
- In the 17th Century, Leibniz Dreamed of a Machine That Could Calculate Ideas
- Andrey Markov & Claude Shannon Counted Letters to Build the First Language-Generation Models
- Why People Demanded Privacy to Confide in the World’s First Chatbot
- In 2016, Microsoft’s Racist Chatbot Revealed the Dangers of Online Conversation
- For Centuries, People Dreamed of a Machine That Could Produce Language. Then OpenAI Made One
- history of natural language processing
Virtual assistants
- Apple / Siri
- Microsoft
- Alexa Developer Official Site / Amazon Alexa Voice AI
- Алиса — голосовой помощник от компании Яндекс
Wikipedia
- Category:Virtual assistants
- Generative Pre-trained Transformer 3 (GPT-3)
- Computational lexicology is a branch of computational linguistics, which is concerned with the use of computers in the study of lexicon.
- Lexical Markup Framework standard for natural language processing (NLP) and machine-readable dictionary (MRD) lexicons.
- Natural-language understanding
- Part-of-speech tagging also called grammatical tagging is the process of marking up a word in a text (corpus) as corresponding to a particular part of speech, based on both its definition and its context.
- Частеречная разметка этап автоматической обработки текста, задачей которого является определение части речи и грамматических характеристик слов в тексте (корпусе) с приписыванием им соответствующих тегов.
- Latent space latent feature space or embedding space, is an embedding of a set of items within a manifold in which items resembling each other are positioned closer to one another in the latent space.
Books
- GPT-3. Building Innovative NLP Products Using Large Language Models by Sandra Kublik and Shubham Saboo - 148 pages
- Natural Language Processing with Flair. A practical guide to understanding and solving NLP problems with Flair by Tadej Magajna - 200 pages
- Introduction to Transformers for NLP. With the Hugging Face Library and Models to Solve Problems by Shashank Mohan Jain - 165 pages
Neural nets
- YaLM-100B