Search Results for "language learning" - Page 25
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Showing 934 open source projects for "language learning"
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CodeSearchNet
Datasets, tools, and benchmarks for representation learning of code
CodeSearchNet is a large-scale dataset and research benchmark designed to advance the development of systems that retrieve source code using natural language queries. The project was created through collaboration between GitHub and Microsoft Research and aims to support research on semantic code search and program understanding. The dataset contains millions of pairs of source code functions and corresponding documentation comments extracted from open-source repositories. These pairs allow machine learning models to learn relationships between natural language descriptions and programming code. ... -
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Graph4NLP
Graph4nlp is the library for the easy use of Graph Neural Networks
Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP). It provides both full implementations of state-of-the-art models for data scientists and also flexible interfaces to build customized models for researchers and developers with whole-pipeline support. Built upon highly-optimized runtime libraries including DGL , Graph4NLP has both high running efficiency and great extensibility. -
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IoT Technical Guide
IoT Technical Guide - Building a High-Performance IoT Platform
IoT Technical Guide is a Chinese-language learning repository for understanding how high-performance Internet of Things platforms are designed and built. It walks readers through the architecture, concepts, and engineering stack behind IoT systems instead of only listing isolated tools. The guide covers topics such as IoT market context, device models, ThingsBoard source-code learning, MQTT broker setup, CoAP services, message peak shaving, data modeling, and database selection. ... -
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90DaysOfDevOps
The journey towards a better foundational knowledge of DevOps
...The goal is to take 90 days, 1 hour a day, to tackle over 13 areas of DevOps to foundational knowledge. This will not cover all things DevOps but it will cover the areas that I feel will benefit my learning and understanding overall. What is and why do we use DevOps. Learning a Programming Language. Knowing Linux Basics. Understand Networking. Stick to one Cloud Provider. Use Git Effectively. Automate Configuration Management. Learn Infrastructure as Code. And much more! -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Hugging Face Transformer
CPU/GPU inference server for Hugging Face transformer models
Optimize and deploy in production Hugging Face Transformer models in a single command line. At Lefebvre Dalloz we run in-production semantic search engines in the legal domain, in the non-marketing language it's a re-ranker, and we based ours on Transformer. In that setup, latency is key to providing a good user experience, and relevancy inference is done online for hundreds of snippets per user query. Most tutorials on Transformer deployment in production are built over Pytorch and FastAPI.... -
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go-study-index
Go language learning materials index
go-study-index is a comprehensive, community-maintained index of Go learning resources and communities, primarily oriented toward Chinese-speaking developers. It was created because a previous index of resources had gone out of date for over three years, and the author wanted a fresher, living catalog that others could update via fork and pull request. The README is structured into sections for communities, navigation sites, learning materials, tools, cloud platforms, newsletters, videos, and even job resources. ... -
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Awesome Decision Tree Papers
A collection of research papers on decision, classification, etc.
A collection of research papers on decision, classification and regression trees with implementations. -
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Java Core Learning Example
Examples of learning and accumulating Java core technologies
Java Core Learning Example is an educational Java repository focused on core language concepts and practical examples for beginners and developers reviewing fundamentals. It covers syntax, object-oriented programming, collections, I/O, NIO, reflection, runtime type information, threading, networking, and initialization behavior. Java 8 material includes lambda expressions and the Stream API. -
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Ferret
Ferret is a web scraping system
Ferret is a web scraping system. It aims to simplify data extraction from the web for UI testing, machine learning, analytics and more. ferret allows users to focus on the data. It abstracts away the technical details and complexity of underlying technologies using its own declarative language. It is extremely portable, extensible, and fast. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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TeLOS Linux
humbly smart Operating System - Debian derivative
TeLOS is a new, universal Linux distribution, a carefully customized derivative of Debian bullseye / sid with KDE Plasma Desktop Environment featuring an unbiased selection of useful applications and services. You may find TeLOS Linux to be snappy, lightweight, ready for work or fun straight out of the box and easily configurable. This Operating System is freely distributed and honors free, open source software development. Nevertheless, some non-free proprietary packages are included to... -
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python-tutorial
Practical Python tutorials, including Python basics
python-tutorial is a practical Python learning repository that collects examples for everyday programming tasks. It covers Python fundamentals, advanced language features, object-oriented programming, multithreading, databases, data science, Flask development, web crawling, and utility scripting. The project is intended for beginners learning Python and for working developers who want reference implementations for common scripts. -
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MTBook
Machine Translation: Foundations and Models
This is a tutorial, the purpose is to introduce the basic knowledge and modeling methods of machine translation systematically, and on this basis, discuss some cutting-edge technologies of machine translation (formerly known as "Machine Translation: Statistical Modeling and Deep Learning") method"). Its content is compiled into a book, which can be used for the study of senior undergraduates and graduate students in computer and artificial intelligence related majors, and can also be used as reference material for researchers related to natural language processing, especially machine translation. This book is written in tex, and all source codes are open. ... -
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Mocking Bird
Clone a voice in 5 seconds to generate arbitrary speech in real-time
MockingBird is an open-source voice cloning and real-time speech generation toolkit that lets you clone a speaker’s voice from a short audio sample (reportedly as little as 5 seconds) and then synthesize arbitrary speech in that voice. It builds on deep-learning based TTS / voice-cloning technology (in the lineage of projects such as Real-Time-Voice-Cloning), but extends it with support for Mandarin Chinese and multiple Chinese speech datasets — broadening its applicability beyond English.... -
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Spring Boot Learning
Spring Boot Tutorial Source Code
SpringBootLearning is a collection of sample applications that accompanies an unofficial Chinese-language Spring Boot tutorial series. It starts with basic project creation and configuration, then expands into common backend development tasks. The examples cover JDBC, JPA, MyBatis, MongoDB, Redis, transactions, caching, and several messaging technologies. Additional modules demonstrate REST documentation, Swagger, file uploads, form validation, scheduled tasks, asynchronous methods, and... -
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Aquila DB
An easy to use Neural Search Engine
Aquila DB is a Neural search engine. In other words, it is a database to index Latent Vectors generated by ML models along with JSON Metadata to perform k-NN retrieval. It is dead simple to set up, language-agnostic, and drop in addition to your Machine Learning Applications. Aquila DB, as of current features is a ready solution for Machine Learning engineers and Data scientists to build Neural Information Retrieval applications out of the box with minimal dependencies. -
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fairseq-lua
Facebook AI Research Sequence-to-Sequence Toolkit
...The framework implements sequence-to-sequence models with attention, beam search decoding, and distributed training, providing a research platform for exploring translation, summarization, and language modeling. Its modular design made it easy to prototype new architectures by modifying encoders, decoders, or attention mechanisms. Although now deprecated in favor of the PyTorch rewrite, fairseq-lua played a key role in advancing large-scale NMT systems, such as early versions of Facebook’s production translation models. It remains an important historical reference for neural sequence learning frameworks. -
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Java-based language learning utility for vocabulary augmentation. - Insert words ( suggestions from Google ) - Make tests - Search and filter - Export/Import ( PDF, XML, XLS) - Conjugate - View corresponding images.
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nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
nlp-tutorial is an educational repository that implements influential natural language processing models in concise PyTorch examples. Most implementations use fewer than 100 lines of executable code, making the architectures easier to inspect and modify. The curriculum begins with neural language models, Word2Vec, and FastText. It then covers TextCNN, recurrent networks, LSTM, bidirectional LSTM, sequence-to-sequence learning, and attention. -
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erlang-bookmarks
All about erlang programming language [powerd by community]
erlang-bookmarks is a curated open-source collection of useful resources for developers working with the Erlang programming language. Rather than being a software library, the repository functions as a community-maintained knowledge hub that aggregates articles, tools, tutorials, and documentation links relevant to Erlang development. The project is intended to help both newcomers and experienced engineers quickly discover high-quality learning materials and ecosystem references. ... -
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FARM
Fast & easy transfer learning for NLP
...Easy fine-tuning of language models to your task and domain language. AMP optimizers (~35% faster) and parallel preprocessing (16 CPU cores => ~16x faster). Modular design of language models and prediction heads. Switch between heads or combine them for multitask learning. Full Compatibility with HuggingFace Transformers' models and model hub. Smooth upgrading to newer language models. -
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Arraymancer
A fast, ergonomic and portable tensor library in Nim
Arraymancer is a tensor and deep learning library for the Nim programming language, designed for high-performance numerical computations and machine learning applications. -
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Kashgari
Kashgari is a production-level NLP Transfer learning framework
Kashgari is a simple and powerful NLP Transfer learning framework, build a state-of-art model in 5 minutes for named entity recognition (NER), part-of-speech tagging (PoS), and text classification tasks. -
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Microsoft Bot Framework SDK
Tool for building conversation applications
Bot Framework provides the most comprehensive experience for building conversation applications. With the Bot Framework SDK, developers can build bots that converse free-form or with guided interactions including using simple text or rich cards that contain text, images, and action buttons. Developers can model and build sophisticated conversation using their favorite programming languages including C#, JS, Python and Java or using Bot Framework Composer, an open-source, visual authoring... -
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libpostal
A C library for parsing/normalizing street addresses around the world
A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data. libpostal is a C library for parsing/normalizing street addresses around the world using statistical NLP and open data. The goal of this project is to understand location-based strings in every language, everywhere. Addresses and the locations they represent are essential for any application dealing with maps (place search, transportation, on-demand/delivery services,... -
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SimCSE
SimCSE: Simple Contrastive Learning of Sentence Embeddings
SimCSE (Simple Contrastive Learning of Sentence Embeddings) is a machine learning framework for training sentence embeddings using contrastive learning. It improves representation learning for NLP tasks.
