This article discusses the difference between deep learning and NLP (natural language processing), as well as common deep learning frameworks for NLP applications.
Deep Learning...
Feature engineering is a crucial stage in Natural Language Processing (NLP) since it structures raw text data for machine learning algorithms. Most computers and...
This blog discusses machine learning in natural language processing (NLP) and covers topics such as what is machine learning, key concepts and techniques, applications...
Word Embedding NLP
In Natural Language Processing, word embeddings are a feature learning technique that maps vocabulary words to vectors of real numbers. Known as...
The contrast between generative and discriminative models is important for NLP tasks like sequence prediction and parsing.
The two categories of models are broken out...
Dependency grammar And Dependency parsing
What is Dependency Grammar?
One important framework for explaining the syntactic structure of sentences is dependency grammar. Dependency grammar does not...
Treebank NLP
Treebanks are corpora with linguistic annotations that go beyond part-of-speech labelling and incorporate some form of syntactic analysis. These are sets of sentences,...
Standard Context-Free Grammars (CFGs) used in natural language processing, especially for statistical parsing, are significantly extended by Probabilistic Context-Free Grammars (PCFGs), also referred to...
Parsing Algorithms
Syntactic parsing, which involves mapping a string of words to its parse tree or giving a phrase a syntactic structure based on a...