Search Results for "python language" - Page 66
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Showing 2504 open source projects for "python language"
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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,... -
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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,... -
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mazeman
A scriptable 2d randomizable maze game
Mazeman is an original puzzle game, somewhat like "chip's challenge" except it can generate new randomized puzzles from a carefully balanced array of elements. The objective is to find the gems amongst the other dynamic maze elements. A very terse and powerful scripting language and an integrated script debugger enable users to generate their own maze designs. Maze is a mesmerizing addictive and fascinating puzzle with a deceptively simple premise. Scripts allow new players to acquire... -
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wtfpython
Exploring and understanding Python through surprising snippets
Python, being a beautifully designed high-level and interpreter-based programming language, provides us with many features for the programmer's comfort. But sometimes, the outcomes of a Python snippet may not seem obvious at first sight. Here's a fun project attempting to explain what exactly is happening under the hood for some counter-intuitive snippets and lesser-known features in Python. -
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GraalVM
Run programs faster anywhere
GraalVM is a high-performance multilingual runtime. It is designed to accelerate the execution of applications written in Java and other JVM languages while also providing runtimes for JavaScript, Ruby, Python, etc. Increase application throughput and reduce latency. Compile applications into small self-contained native binaries. Seamlessly use multiple languages and libraries. Advanced optimizing compiler that generates fast lean code which requires fewer compute resources. Native binaries... -
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PyResParser
A simple resume parser used for extracting information from resumes
PyResParser is a simple resume parser that extracts information from resumes, aiding in the automation of resume-processing tasks. -
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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. -
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Miasm
Reverse engineering framework in Python
The Miasm intermediate representation is used for multiple task: emulation through its jitter engine, symbolic execution, DSE, program analysis, but the intermediate representation can be a bit hard to read. We will present in this article new tricks Miasm has learned in 2018. Among them, the SSA/Out-of-SSA transformation, expression propagation and high-level operators can be joined to “lift” Miasm IR to a more human-readable language. We use graphviz to illustrate some graphs. Its layout... -
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Dragonfire
The open-source virtual assistant for Ubuntu based Linux distributions
Dragonfire is the open-source virtual assistant project for Ubuntu-based Linux distributions. Her main objective is to serve as a command and control interface to the helmet user. So that you will be able to give orders just by using your voice commands and your eye movements. That makes the helmet handsfree. We are planning to ship Dragonfire as a preinstalled software package on DragonOS Linux Distribution. DragonOS will be a Linux distribution specially designed for the helmet. It will... -
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Vega Strike is a 3d OpenGL Action Space Sim for Win/Lin/Mac allowing players to trade, bounty hunt, or explore in a vast universe. Active development is now on https://github.com/vegastrike and on http://www.vega-strike.org Vega Strike is mod ready and network playable.
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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. A mirror of this... -
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show-me-the-code
Python Workbook, a small program every day
Show Me the Code is a Chinese-language programming exercise collection centered on completing one small practical challenge at a time. Although presented as a Python workbook, many of the exercises can be implemented in other programming languages. The challenges intentionally avoid routine textbook exercises and instead use tasks that resemble small real-world programming problems. -
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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. -
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Budou
Budou is an auto organizer tool for beautiful line breaking in CJK
...These spans can be styled with CSS to ensure smooth, visually coherent line breaks without splitting words or phrases. The tool supports multiple segmentation backends, including Google Cloud Natural Language API, MeCab, and TinySegmenter, enabling flexibility for both cloud-based and offline processing. Budou can be used via command line, in Python scripts, or integrated into web applications, and it provides advanced options such as caching and entity recognition for improved segmentation accuracy. -
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Twint
An advanced Twitter scraping & OSINT tool written in Python
Twint is an advanced open-source Twitter scraping and OSINT tool written in Python that extracts tweets, user data, followers, likes, and more—without relying on Twitter’s API—making it highly useful for researchers, analysts, and hobbyists who want to bypass rate limits and access public Twitter data. -
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gpt2-client
Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.
GPT-2 is a Natural Language Processing model developed by OpenAI for text generation. It is the successor to the GPT (Generative Pre-trained Transformer) model trained on 40GB of text from the internet. It features a Transformer model that was brought to light by the Attention Is All You Need paper in 2017. The model has 4 versions - 124M, 345M, 774M, and 1558M - that differ in terms of the amount of training data fed to it and the number of parameters they contain. Finally, gpt2-client is a... -
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Deep Learning with PyTorch
Latest techniques in deep learning and representation learning
This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course. To be able to follow the exercises, you are going to need a laptop with Miniconda (a minimal version of Anaconda) and several Python packages installed. The following instruction would work as is for Mac or Ubuntu Linux users, Windows users would need to install and work in the Git BASH terminal. ... -
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mypalm
Palm programming language
Palm is a programming language developped by Palm inc, It has the aim to implement an innovative language flexible for users and easy to use that could be applied to a wide range of fields. It is programmed in python and its first version root.0.0.1 is available since November 20 2019 -
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AES Everywhere
Cross Language AES 256 Encryption Library
AES Everywhere is Cross Language Encryption Library that provides the ability to encrypt and decrypt data using a single algorithm in different programming languages and on different platforms. This is an implementation of the AES algorithm, specifically CBC mode, with 256-bit key length and PKCS7 padding. It implements OpenSSL-compatible cryptography with randomly generated salt. -
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Microsoft Python Language Server
Microsoft Language Server for Python
Microsoft Python Language Server implements the Language Server Protocol. Its primary clients are the Python extension for VS Code and Python Tools for Visual Studio. Feel free to file issues or ask questions on our issue tracker, and we welcome code contributions. Linting can be controlled via the user configuration. In VS Code, this is settings.json. -
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InferSent
InferSent sentence embeddings
InferSent is a supervised sentence embedding method that learns universal representations from Natural Language Inference data and transfers well to many downstream tasks. It uses a BiLSTM encoder with max-pooling to produce fixed-length sentence vectors that capture semantics beyond bag-of-words statistics. Trained on large NLI datasets, the embeddings generalize across tasks like sentiment analysis, entailment, paraphrase detection, and semantic similarity with simple linear classifiers.... -
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OpenSource solution to download your SKYPE contact list in CSV format. https://github.com/SkpyBackup/SkpyBackup Using: https://skpy.t.allofti.me https://pandas.pydata.org https://pypi.org/project/auto-py-to-exe https://visualstudio.microsoft.com/pt-br/vs/community Get this data from your contact list: *id *name *location *language *avatar *mood *phones *birthday *authorised *blocked *favourite
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MMF
A modular framework for vision & language multimodal research
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that... -
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Coursebook
Introductory Systems Programming Textbook for University of Illinois
Welcome to the systems programming coursebook! This repository houses a high-quality, open-source introductory systems programming textbook used by the CS 341: System Programming course at the University of Illinois at Urbana-Champaign The book assumes that you have taken a programming language course and are familiar with assembly instructions. All of the code and instruction will be in C, as it is the de-facto language of the Linux Kernel. -
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nonechucks
Deal with bad samples in your dataset dynamically
nonechucks is a library that provides wrappers for PyTorch's datasets, samplers and transforms to allow for dropping unwanted or invalid samples dynamically. What if you have a dataset of 1000s of images, out of which a few dozen images are unreadable because the image files are corrupted? Or what if your dataset is a folder full of scanned PDFs that you have to OCRize, and then run a language detector on the resulting text, because you want only the ones that are in English? Or maybe you...
