Deep networks work by learning complex, often hierarchical internal representations of input data. These form a kind of functional language the network uses to describe the data.
Language can emerge from tasks like object recognition: has pointy ears, whiskers, tail => cat.
This relates to Wittgenstein’s "language-game" in Philosophical Investigations, where a functional language emerge from simple tasks before defining a vocabulary.
The visual vocabulary of a convolutional neural network seems to emerge from low level features such as edges and orientations, and builds up textures, patterns and composites, … and builds up even further into complete objects: houses, dogs, etc.
Source: NeurIPS 2018“Unsupervised Deep Learning” Tutorial – Part 1 by Alex Graves - https://lnkd.in/eXjxA2n
#artificialintelligence #deeplearning #language #machinelearning
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN
Language can emerge from tasks like object recognition: has pointy ears, whiskers, tail => cat.
This relates to Wittgenstein’s "language-game" in Philosophical Investigations, where a functional language emerge from simple tasks before defining a vocabulary.
The visual vocabulary of a convolutional neural network seems to emerge from low level features such as edges and orientations, and builds up textures, patterns and composites, … and builds up even further into complete objects: houses, dogs, etc.
Source: NeurIPS 2018“Unsupervised Deep Learning” Tutorial – Part 1 by Alex Graves - https://lnkd.in/eXjxA2n
#artificialintelligence #deeplearning #language #machinelearning
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN
Python - Python NLP Libraries
TextBlob - Providing a consistent API for diving into common natural language processing (NLP) tasks. Stands on the giant shoulders of Natural Language Toolkit (NLTK) and Pattern, and plays nicely with bot.
spaCy - Industrial strength NLP with Python and Cython
textacy - Higher level NLP built on spaCy
gensim - Python library to conduct unsupervised semantic modelling from plain text
scattertext - Python library to produce d3 visualizations of how language differs between corpora
AllenNLP - An NLP research library, built on PyTorch, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks.
PyTorch-NLP - NLP research toolkit designed to support rapid prototyping with better data loaders, word vector loaders, neural network layer representations, common NLP metrics such as BLEU.
Rosetta - Text processing tools and wrappers (e.g. Vowpal Wabbit).
PyNLPl - Python Natural Language Processing Library. General purpose NLP library for Python. Also contains some specific modules for parsing common NLP formats, most notably for FoLiA, but also ARPA language models, Moses phrasetables, GIZA++ alignments.
#naturallanguage #machinelearning #ai #language #nlp #spacy #pytorch
✴️ @AI_Python_EN
TextBlob - Providing a consistent API for diving into common natural language processing (NLP) tasks. Stands on the giant shoulders of Natural Language Toolkit (NLTK) and Pattern, and plays nicely with bot.
spaCy - Industrial strength NLP with Python and Cython
textacy - Higher level NLP built on spaCy
gensim - Python library to conduct unsupervised semantic modelling from plain text
scattertext - Python library to produce d3 visualizations of how language differs between corpora
AllenNLP - An NLP research library, built on PyTorch, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks.
PyTorch-NLP - NLP research toolkit designed to support rapid prototyping with better data loaders, word vector loaders, neural network layer representations, common NLP metrics such as BLEU.
Rosetta - Text processing tools and wrappers (e.g. Vowpal Wabbit).
PyNLPl - Python Natural Language Processing Library. General purpose NLP library for Python. Also contains some specific modules for parsing common NLP formats, most notably for FoLiA, but also ARPA language models, Moses phrasetables, GIZA++ alignments.
#naturallanguage #machinelearning #ai #language #nlp #spacy #pytorch
✴️ @AI_Python_EN