Search Results for "text processing" - Page 16
Sort By:
Showing 1237 open source projects for "text processing"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
CSVfix
Command-line tool specifically designed to deal with CSV data
...Unfortunately, the CSV files you are given, or are required to produce, never seem to be in quite the right format for your particular business application. And because of the structure of CSV records, using standard text processing tools like sed, awk and perl is not as simple as it might be. Usage: http://csvfix.byethost5.com/csvfix15/csvfix.html?csvfix.html?Usage.html?i=1&i=2 CSVfix aims to provide a solution to these problems. It is a command-line stream editor specifically designed to deal with CSV data. With it you can, among other things: -
2
DeText
A Deep Neural Text Understanding Framework
DeText is a Deep Text understanding framework for NLP-related ranking, classification, and language generation tasks. It leverages semantic matching using deep neural networks to understand member intents in search and recommender systems. As a general NLP framework, DeText can be applied to many tasks, including search & recommendation ranking, multi-class classification and query understanding tasks. -
3
A collection of small utilities for: data extraction (text or binary files), data buffering, message queue control, column addition, date/time manipulation, and data recovery testing.
-
4
NLP-Models-Tensorflow
Gathers machine learning and Tensorflow deep learning models for NLP
NLP-Models-Tensorflow is a collection of natural language processing model implementations built using the TensorFlow deep learning framework. The repository provides numerous examples of neural network architectures used in modern NLP research and applications, including text classification, language modeling, machine translation, and sentiment analysis. Each model implementation is designed to illustrate how common NLP architectures operate, such as recurrent neural networks, convolutional models for text processing, and transformer-style attention mechanisms. ... -
Earn up to 16% annual interest with Nexo.Put idle assets to work with competitive interest rates, borrow without selling, and trade with precision. All in one platform. Geographic restrictions, eligibility, and terms apply.
-
5
Leseratte is a Java parser for German written language. Currently, it contains a German lexicon (based on the Wiktionary), inflexion rules, a grammar and a parser. (Semantics component planned.) Usable as a Java library, also provides a graphical UI.
-
6
Delta ML
Deep learning based natural language and speech processing platform
...It helps you to train, develop, and deploy NLP and/or speech models. Use configuration files to easily tune parameters and network structures. What you see in training is what you get in serving: all data processing and features extraction are integrated into a model graph. Text classification, named entity recognition, question and answering, text summarization, etc. Uniform I/O interfaces and no changes for new models. -
7
Xi Editor
A modern editor with a backend written in Rust
xi Editor (often styled “Xi”) is a project to build a modern, high-performance text editor designed for large files, extensibility, and native UI integration. Its architecture splits a thin UI layer from a high-performance core engine (written in Rust) that handles buffer editing, syntax highlighting, undo/redo, searching, and background processing asynchronously. This separation lets the core focus on speed and concurrency, while multiple frontends (macOS, GTK, web) handle rendering, input, and platform bridging. ... -
8
Euler
A distributed graph deep learning framework.
As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle. -
9
PyCBC
Learn how to use PyCBC to analyze gravitational-wave data
PyCBC is a software developed by a collaboration of LIGO, Virgo, and independent scientists. It is open source and freely available. We use PyCBC in the detection of gravitational waves from binary mergers such as GW150914. These examples explore how to analyze gravitational wave data, how we find potential signals and learn about them. Many of these tutorials will require you to make edits to config files as part of their exercises. At the moment this isn't easy to do on services like... -
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
-
10
fastText
Library for fast text classification and representation
FastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices. ext classification is a core problem to many applications, like spam detection, sentiment analysis or smart replies. In this tutorial, we describe how to build a text classifier with the fastText tool. The goal of text classification is to assign documents (such as... -
11
Forms
An easy way to create, parse and validate forms in node.js
...It allows developers to define form schemas using a declarative API, specifying fields, validation rules, and data transformations in a consistent format. The library supports a wide range of input types, including text, numbers, dates, and custom fields, making it adaptable to different application needs. It includes built-in validation mechanisms that ensure user input meets specified constraints before being processed. Forms also provides utilities for rendering HTML form elements, reducing the need for manual template coding. It integrates with popular Node.js web frameworks, enabling seamless handling of form submissions and data processing. ... -
12
BRIC
BRIC is a powerful tool for batch image processing.
Bric is a cross-platform batch image processor. You can convert, resize, rotate and add watermark to your images. Multiple file types are supported for input and output. The project started back in 2011 and was maintained for a couple of years. In 2020 BRIC is again in active development, so some of the features written below might be outdated. Please be patient, until everything is reviewed and rewritten. -
13
Data Science at the Command Line
Data science at the command line
...To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools, useful whether you work with Windows, macOS, or Linux. You’ll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you’re comfortable processing data with Python or R, you’ll learn how to greatly improve your data science workflow by leveraging the command line’s power. -
14
NLP Best Practices
Natural Language Processing Best Practices & Examples
In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive business adoption of artificial intelligence (AI) solutions. In the last few years, researchers have been applying newer deep learning methods to NLP. Data scientists started moving from traditional methods to state-of-the-art (SOTA) deep neural network (DNN) algorithms which use language models pretrained on large text corpora. -
15
Programa para generar documentos HTML con expresiones matemáticas incrustadas, procesadas con Maxima (maxima.sourceforge.net).
-
16
YouTokenToMe
Unsupervised text tokenizer focused on computational efficiency
YouTokenToMe is a fast and efficient unsupervised text tokenization library designed for training subword embeddings, particularly useful for NLP models. -
17
FastoCloud PRO
IPTV/NVR/CCTV/Video cloud https://fastocloud.com
IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch Mozaic Many Outputs Physical Inputs Streaming Protocols File Formats Presets Vods/Series server-side support Pay per view channels Channels on demand HTTP Live Streaming (HLS) server-side support Public API, client server communication via JSON RPC Protocol gzip compression Deep learning video analysis Supported deep learning frameworks: Tensorflow NCSDK Caffe ML Hardware: -
18
AhoCorasickDoubleArrayTrie
An extremely fast implementation of Aho Corasick algorithm
...It is designed for fast keyword scanning across large texts, where you want to search for many patterns simultaneously and efficiently. The core idea is to build an automaton from a dictionary of patterns, then stream through input text to emit matches with minimal overhead. By using a double-array trie representation, the project emphasizes performance and memory efficiency compared to simpler pointer-heavy trie structures, which can matter a lot for large dictionaries or latency-sensitive services. This makes it a strong fit for tasks like content filtering, entity/term spotting, dictionary-based annotation, or high-throughput log/text processing. ... -
19
cocoNLP
A Chinese information extraction tool
cocoNLP is a lightweight natural-language processing toolkit geared toward practical information extraction from raw text, especially for Chinese and mixed Chinese–English content. Instead of requiring a heavy pipeline, it focuses on quick wins such as extracting names, places, organizations, emails, phone numbers, and dates directly from unstructured sentences. The project blends pattern-based methods with NLP heuristics, giving developers dependable results for real-world texts like chats, comments, and user-generated content. ... -
20
Anaphraseus is a CAT (Computer Aided Translation) tool, OpenOffice.org 2-3 macro set for OpenOffice/LibreOffice Writer similar to famous Wordfast. It works with the Wordfast Translation Memory format (*.TXT), and supports text segmentation.
-
21
PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. -
22
VoiceShot API - PHP SDK
PHP SDK for processing phone calls and SMS through the VoiceShot API.
VoiceShot's API allows you to quickly integrate both incoming and outgoing phone calling and text messaging services into your applications. From your own applications, you can easily place and receive interactive telephone calls and text messages. Put callers in touch with the data and people they want when they want it. Send notification phone calls and text messages, automate customer service calls/texts, provide order status and integrate with your own custom applications to provide... -
23
VoiceShot API - .NET SDK
.NET SDK for processing phone calls and SMS through the VoiceShot API.
VoiceShot's API allows you to quickly integrate both incoming and outgoing phone calling and text messaging services into your applications. From your own applications, you can easily place and receive interactive telephone calls and text messages. Put callers in touch with the data and people they want when they want it. Send notification phone calls and text messages, automate customer service calls/texts, provide order status and integrate with your own custom applications to provide... -
24
VoiceShot API - ASP SDK
ASP SDK for processing phone calls and SMS through the VoiceShot API.
VoiceShot's API allows you to quickly integrate both incoming and outgoing phone calling and text messaging services into your applications. From your own applications, you can easily place and receive interactive telephone calls and text messages. Put callers in touch with the data and people they want when they want it. Send notification phone calls and text messages, automate customer service calls/texts, provide order status and integrate with your own custom applications to provide... -
25
Steganography
Steganography library for Processing
V1.0.2 compatible with both Processing 2 & 3 Hide your images and text in plain sight. A library for Processing that can embed text and images into a carrier image. The hidden image or text is encrypted for additional security and requires a password or better still a pass phrase to retrieve and decrypt the hidden message. There is no source code difference between 1.0.1 and 1.0.2 it simply corrects the library URL in the supporting documentation used by the Processing Foundation.
