Leveraging Deep Learning for Sentiment Analysis — TL;DR: Sentiment analysis, also known as opinion mining, is the process of computationally identifying and categorizing the subjective information contained in natural language text. …

Discover the basics of Transformer-based models and learn how to generate powerful sentence embeddings using them in Spark NLP — TL; DR: Sentence embeddings are a powerful tool in natural language processing that help analyze and understand language. Transformers, a type of neural network architecture, are a popular method for generating these embeddings. …

Building a Stop Words Removal Pipeline in Spark NLP — TL;DR: Stopwords removal in natural language processing (NLP) is the process of eliminating words that occur frequently in a language but carry little or no meaning. …

Why is there a need for Spark NLP? — Natural Language Processing (NLP) is a subfield of Artificial Intelligence (AI) that focuses on the interaction between computers and human language. It involves the development and application of computational algorithms and models to understand, analyze, and generate human language in a way that is meaningful and useful. NLP is a…

Supercharge rule-based sentiment analysis for large-scale datasets with the power of Spark NLP. — TL; DR: Rule-based sentiment analysis in Natural Language Processing (NLP) is a method of sentiment analysis that uses a set of manually-defined rules to identify and extract subjective information from text data. Using Spark NLP, it is possible to analyze the sentiment in a text with high accuracy. Sentiment analysis…

Discover how to use transformers-based models in Spark NLP for state-of-the-art text classification — TL; DR: Sequence classification with transformers refers to the task of predicting a label or category for a sequence of data, which can include text as well as other types of data such as audio, images, or time series. …

An Introduction to Normalization Techniques in Spark NLP — TL;DR: The Normalizer annotator in Spark NLP performs text normalization on data. It is used to remove all dirty characters from text following a regex pattern, convert text to lowercase, remove special characters, punctuation, and transform words based on a provided dictionary. The Normalizer annotator in Spark NLP is often…

Discover the incredible capabilities of Spark NLP for advanced Question Answering models. — TL;DR: Question answering can be defined as building systems for the process of retrieving information from a given knowledge source or corpus and generating an appropriate response to the questions asked by humans in a natural language. Spark NLP provides several pre-trained models that can be used for question answering.

Transform Your Texts into Powerful Vectors for Machine Learning with Spark NLP and Python — TL; DR: Word embeddings are considered as a type of representation used in natural language processing (NLP) to capture the meaning of words in a numerical form. …