Search Results for "sentence"

spaCy is a library built on the very latest research for advanced Natural Language Processing (NLP) in Python and Cython. Since its inception it was designed to be used for real world applications-- for building real products and gathering real insights. It comes with pretrained statistical models and word vectors, convolutional neural network models, easy deep learning integration and so much more. spaCy is the fastest syntactic parser in the world according to independent benchmarks, with...

Venom is a high-performance system developed with JavaScript to create a bot for WhatsApp, support for creating any interaction, such as customer service, media sending, sentence recognition based on artificial intelligence and all types of design architecture for WhatsApp. It's a high-performance alternative API to whatzapp, you can send, text messages, files, images, videos and more. Remember, the API was developed on a platform called RESTful Web services, providing interoperability between computer systems on the Internet. ...

Typed.js is a library that types. Enter in any string, and watch it type at the speed you've set, backspace what it's typed, and begin a new sentence for however many strings you've set. Rather than using the strings array to insert strings, you can place an HTML div on the page and read from it. This allows bots and search engines, as well as users with JavaScript disabled, to see your text on the page. You can pause in the middle of a string for a given amount of time by including an escape character. ...

Its task is simple: It tells you which language some provided textual data is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages.

...Because the interface is minimal, researchers can plug in encoders from any framework or language model and obtain a broad evaluation with little glue code. SentEval helped establish common baselines and reporting conventions in the sentence-representation community, reducing friction when comparing new methods.

...The effects are stunning - Concordia is able to do simple substring lookup at the pace of 5000 queries per second (on personal PC) - a speed which can not be achieved by any other search library. Moreover, Concordia can perform its own "concordia search". For a given input sentece, all substring matches covering this sentence are retrieved. This project now contains fully functional Concordia search library. In the near future, it will be extended by concordia-server: ligthweight, robust web server providing corpora search functionalities

The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution filters to extract n-gram features that are then pooled and fed into a classifier. The project includes scripts for training, evaluation, and data handling, making it easy to run experiments on datasets such as movie reviews or other labeled text collections. ...

Deeplearning-papernotes is an implementation of Convolutional Neural Networks for sentence and text classification in TensorFlow, based on a well-known research paper that applies CNN architectures to natural language processing tasks with strong performance in sentiment analysis and similar classification problems. The repository provides the complete network definition, including an embedding layer to convert words into dense representations, convolution and max-pooling layers to extract informative features, and a final softmax classifier to distinguish between target classes. ...

An Expression Parser and Evaluator result in JSON object. Written in Pascal. 表达式的解析和求值是一个应用面非常广的功能。JSON格式因其简明、易于操作，使用面日渐广泛。本项目将表达式分析的结果存放在JS