Search Results for "machine language" - Page 20
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Showing 768 open source projects for "machine language"
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levin
in-memory key value server with fuzzy search capabilities
Levin is an event-based key/value server based on radix-tree (space optimized trie). Key search can be performed with an approximate key matching algorithm based on Levenshtein edit distance. -
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Config Tool
a GUI for configure glftpd and zipscript-ng/backupscript settings
Let you configure settings for glftpd such as user permissions and provides some special programs for backup files from glftpd server as well as uploaded ones. -
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GluonNLP
NLP made easy
GluonNLP is a toolkit that helps you solve NLP problems. It provides easy-to-use tools that helps you load the text data, process the text data, and train models. To facilitate both the engineers and researchers, we provide command-line-toolkits for downloading and processing the NLP datasets. Gluon NLP makes it easy to evaluate and train word embeddings. Here are examples to evaluate the pre-trained embeddings included in the Gluon NLP toolkit as well as example scripts for training... -
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Dart
Dart is a client-optimized language for fast apps on any platform
The Dart SDK, including the VM, dart2js, core libraries, and more. Develop with a programming language specialized around the needs of user interface creation. Make changes iteratively, use hot reload to see the result instantly in your running app. Compile to ARM & x64 machine code for mobile, desktop, and backend. Or compile to JavaScript for the web. Mature and complete async-await for user interfaces containing event-driven code, paired with isolate-based concurrency. ... -
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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. ... -
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Multilingual Speech Synthesis
An implementation of Tacotron 2 that supports multilingual experiments
...The second has separate encoders for each language. -
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Delta ML
Deep learning based natural language and speech processing platform
DELTA is a deep learning-based end-to-end natural language and speech processing platform. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users. It helps you to train,... -
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ocapi
C-level driver collection for MSP430 and derivatives
...ocapi is used as the hardware abstraction layer for the MSP430 port of the Takatuka Java virtual machine (JVM). Before it can be used, the library must be built from the sources provided here. The build environment allows for fine grained configuration of the library's functionality and target system. -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
...It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. ... -
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RISC-V BOOM
SonicBOOM: The Berkeley Out-of-Order Machine
The riscv-boom project (also called BOOM or SonicBOOM) implements a high-performance, synthesizable out-of-order RISC-V core written in the Chisel hardware construction language. It targets the RV64GC (i.e. 64-bit with general + compressed + floating point) instruction set and supports features such as virtual memory, caches, atomics, and IEEE-754 floating point. The design is parameterizable, meaning users can tune pipeline widths, buffer sizes, functional units, and other... -
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NLP Best Practices
Natural Language Processing Best Practices & Examples
...The focus of the repository is on state-of-the-art methods and common scenarios that are popular among researchers and practitioners working on problems involving text and language. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in NLP algorithms, neural architectures, and distributed machine learning systems. -
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BookPart2
Interpreter Code for Book Part 2
Source code for the book "Writing an Interpreter for Object Pascal: Part 2 This is the second part of a series that will show you how to write an interactive interpreter in Object Pascal. Part 2 describes the building of the first version of a virtual machine together with a simple assembler. The book combines the virtual machine with the syntax checker for the Rhodus language. Intermediate code is generated directly as the source code is parsed. At the end of Part II, the reader will be a very serviceable interpreter that supports user-defined functions, built-in functions, string, and list support together with a range of looping constructs. ... -
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NLP-progress
Repository to track the progress in Natural Language Processing (NLP)
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks. This document aims to track the progress in Natural Language Processing (NLP) and give an overview of the state-of-the-art (SOTA) across the most common NLP tasks and their corresponding datasets. It aims to cover both traditional and core NLP tasks such as dependency parsing and part-of-speech tagging as well as more recent ones such... -
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fastText
Library for fast text classification and representation
...The goal of text classification is to assign documents (such as emails, posts, text messages, product reviews, etc...) to one or multiple categories. Such categories can be review scores, spam v.s. non-spam, or the language in which the document was typed. Nowadays, the dominant approach to build such classifiers is machine learning, that is learning classification rules from examples. In order to build such classifiers, we need labeled data, which consists of documents and their corresponding categories (or tags, or labels). -
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Weld
High-performance runtime for data analytics applications
Weld is a programming language and runtime designed to improve the performance of data-intensive applications by optimizing computations across multiple libraries. Instead of optimizing individual functions independently, Weld introduces an intermediate representation that allows different frameworks to share optimization opportunities. This approach reduces data movement between libraries and enables the system to generate highly optimized machine code for parallel execution. ... -
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Emojicode
World’s only programming language that’s bursting with emojis
Emojicode is an open-source, full-blown programming language consisting of emojis. As a multi-paradigm language, Emojicode features object orientation, optionals, generics, closures, and protocols. Emojicode compiles native machine code using lots of optimizations that make your code fast. Emojicode comes with a comprehensive set of default packages. And you can easily write your own. We believe that Emojis have expressive force. -
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Top deep learning Github repositories
Top 200 deep learning Github repositories sorted by stars
Top-Deep-Learning is a curated repository that aggregates some of the most influential and widely used deep learning projects available on GitHub. Instead of providing its own machine learning models or frameworks, the project functions as an organized index that helps users discover high-quality deep learning repositories across different application domains. The repository categorizes projects related to neural networks, computer vision, natural language processing, reinforcement learning, and other areas of artificial intelligence. ... -
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Snips NLU
Snips Python library to extract meaning from text
...Behind every chatbot and voice assistant lies a common piece of technology: Natural Language Understanding (NLU). Anytime a user interacts with an AI using natural language, their words need to be translated into a machine-readable description of what they meant. The NLU engine first detects what the intention of the user is (a.k.a. intent), then extracts the parameters (called slots) of the query. The developer can then use this to determine the appropriate action or response. -
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python-is-cool
Cool Python features for machine learning
python-is-cool is an educational repository created by AI researcher Chip Huyen that explores lesser-known features and powerful capabilities of the Python programming language. The project serves as a curated guide to Python techniques that many developers may overlook or hesitate to use due to unfamiliarity. It demonstrates practical language features, idiomatic programming patterns, and useful tricks that can make Python code more expressive, efficient, and elegant. Much of the content is... -
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PRMLT
Matlab code of machine learning algorithms in book PRML
This Matlab package implements machine learning algorithms described in the great textbook: Pattern Recognition and Machine Learning by C. Bishop (PRML). It is written purely in Matlab language. It is self-contained. There is no external dependency. This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). -
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GHC (Glasgow Haskell Compiler)
Mirror of the Glasgow Haskell Compiler
GHC (Glasgow Haskell Compiler) is the leading open-source compiler and interactive environment for the Haskell programming language, supporting the Haskell 2010 standard plus numerous language extensions. It compiles to native machine code (via LLVM or C), and includes the interactive GHCi REPL. For full information on building GHC, see the GHC Building Guide. Here follows a summary - if you get into trouble, the Building Guide has all the answers. For building library documentation, you'll need Haddock. ... -
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Speech Recognition in English & Polish
Speech recognition software for English & Polish languages
Software for speech recognition in English & Polish languages. Basic versions of SkryBot: 1. SkryBot Home Speech (English Language) - https://sourceforge.net/projects/skrybotdomowy/files/ReleasesEnglish/InstalatorSkryBotHomeSpeechDemo-2.6.9.18117.exe/download 2. SkryBot DoMowy (Polish Language) - https://sourceforge.net/projects/skrybotdomowy/files/ReleasesPolish/InstalatorSkryBotDoMowyDemo-2.4.9.18117.exe/download More... -
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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. For example, check out... -
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Texar
Toolkit for Machine Learning, Natural Language Processing
Texar is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. -
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Deep Learning Drizzle
Drench yourself in Deep Learning, Reinforcement Learning
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures! Optimization courses which form the foundation for ML, DL, RL. Computer Vision courses which are DL & ML heavy. Speech recognition courses which are DL heavy. Structured Courses on Geometric, Graph Neural Networks. Section on Autonomous Vehicles. Section on Computer Graphics with ML/DL focus.