Search Results for "python feature selection" - Page 11
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Showing 500 open source projects for "python feature selection"
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HTTP Prompt
An interactive command-line HTTP and API testing client
HTTP Prompt is an interactive command-line HTTP client featuring autocomplete and syntax highlighting. You'll never have to memorize the whole commands and HTTP headers thanks to autocomplete with fuzzy matching. Improve readability by rendering JSON, HTML and commands with 27 builtin color themes, borrowed from Pygments. Designed to work with and built on top of HTTPie, HTTP Prompt makes a perfect companion for HTTPie. Cookie-based authentication made easy as incoming cookies are... -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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cookiecutter-pypackage
audreyfeldroy's Cookiecutter template for a standard Python package
This is audreyfeldroy's Cookiecutter template for a standard Python package. Note that the version hosted on SourceForge is just a clone of the original repository used to test Cookiecutter's SVN feature. It is not recommended to use this version for actual work, as it will not be updated. HTTPS: cookiecutter svn+https://svn.code.sf.net/p/cookiecutter-pypackage/code/trunk/cookiecutter-pypackage SVN RO: cookiecutter svn://svn.code.sf.net/p/cookiecutter-pypackage/code/trunk/cookiecutter-pypackage SSH (requires SourceForge login): cookiecutter svn+ssh://username@svn.code.sf.net/p/cookiecutter-pypackage/code/trunk/cookiecutter-pypackage Original version: https://github.com/audreyfeldroy/cookiecutter-pypackage -
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cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that...
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FixRes
Reproduces results of "Fixing the train-test resolution discrepancy"
FixRes is a lightweight yet powerful training methodology for convolutional neural networks (CNNs) that addresses the common train-test resolution discrepancy problem in image classification. Developed by Facebook Research, FixRes improves model generalization by adjusting training and evaluation procedures to better align input resolutions used during different phases. The approach is simple but highly effective, requiring no architectural modifications and working across diverse CNN... -
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phpsploit
Full-featured C2 framework which silently persists on webserver
Full-featured C2 framework which silently persists on webserver via polymorphic PHP oneliner. The obfuscated communication is accomplished using HTTP headers under standard client requests and web server's relative responses, tunneled through a tiny polymorphic backdoor. Detailed help for any option (help command) Cross-platform on both client and server. CLI supports auto-completion & multi-command. Session saving/loading feature & persistent history. Multi-request support for large... -
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vim-visual-multi
Multiple cursors plugin for vim/neovim
vim-visual-multi is a plugin that brings multi-cursor functionality to Vim and Neovim similar to what many modern editors provide. Instead of only using Vim’s traditional visual or block modes, this plugin allows you to set up multiple cursors (and multiple selection spots) and perform edits simultaneously in several places at once. You can add cursors by selecting words or using vertical cursor movements, then enter insert or normal mode and your commands are replicated across all active... -
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GPlates
Interactive visualization of plate tectonics.
GPlates is a plate-tectonics program. Manipulate reconstructions of geological and paleo-geographic features through geological time. Interactively visualize vector, raster and volume data. PyGPlates is the GPlates Python library. Get fine-grained access to GPlates functionality in your Python scripts. -
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AWS IoT Greengrass Core SDK
SDK to use with functions running on Greengrass Core using Python
The AWS IoT Greengrass Core SDK is meant to be used by AWS Lambda functions running on an AWS IoT Greengrass Core. It will enable Lambda functions to invoke other Lambda functions deployed to the Greengrass Core, publish messages to the Greengrass Core and work with the local Shadow service. To use the AWS IoT Greengrass Core SDK, you must first import the AWS IoT Greengrass Core SDK in your Lambda function as you would with any other external libraries. You then need to create a client for... -
AI-First Supply Chain ManagementLogility is a market-leading provider of AI-first supply chain management solutions engineered to help organizations build sustainable digital supply chains that improve people’s lives and the world we live in. The company’s approach is designed to reimagine supply chain planning by shifting away from traditional “what happened” processes to an AI-driven strategy that combines the power of humans and machines to predict and be ready for what’s coming. Logility’s fully integrated, end-to-end platform helps clients know faster, turn uncertainty into opportunity, and transform the supply chain from a cost center to an engine for growth.
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DeepCluster
Deep Clustering for Unsupervised Learning of Visual Features
DeepCluster is a classic self-supervised clustering-based representation learning algorithm that iteratively groups image features and uses the cluster assignments as pseudo-labels to train the network. In each round, features produced by the network are clustered (e.g. k-means), and the cluster IDs become supervision targets in the next epoch, encouraging the model to refine its representation to better separate semantic groups. This alternating “cluster & train” scheme helps the model... -
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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. -
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Linux-Intelligent-Ocr-Solution
Easy-OCR solution and Tesseract trainer for GNU/Linux
Linux-intelligent-ocr-solution Lios is a free and open source software for converting print in to text using either scanner or a camera, It can also produce text out of scanned images from other sources such as Pdf, Image, Folder containing Images or screenshot. Program is given total accessibility for visually impaired. A Tesseract Trainer GUI is also shipped with this package. Forum : https://groups.google.com/forum/#!forum/lios Video Tutorial :... -
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EasyArch
Arch Linux Installer ISO
A simple yet full featured Archlinux installer ISO. Minimum system requirements- Processor - 2 core 64 bit Ram - 1 GB HDD space - 10 GB If you are looking for another linux distro, then you are at wrong place, this is not a new or separate distribution. It is just a live ISO to provide simple and easy way to get Archlinux up and running in very little time and with or without internet connection. Yes, you read it right, you can install Archlinux without internet with this ISO.... -
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Magnitude
A fast, efficient universal vector embedding utility package
A feature-packed Python package and vector storage file format for utilizing vector embeddings in machine learning models in a fast, efficient, and simple manner developed by Plasticity. It is primarily intended to be a simpler / faster alternative to Gensim but can be used as a generic key-vector store for domains outside NLP. It offers unique features like out-of-vocabulary lookups and streaming of large models over HTTP. -
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Albedo
A recommender system for discovering GitHub repos
Albedo is an open-source recommender system aimed at helping developers discover GitHub repositories by learning from activity signals. It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible... -
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Kopf
A Python framework to write Kubernetes operators
Kopf —Kubernetes Operator Pythonic Framework, is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). -
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PyTorch GAN Zoo
A mix of GAN implementations including progressive growing
PyTorch GAN Zoo is a comprehensive open research toolbox designed for experimenting with and developing Generative Adversarial Networks (GANs) using PyTorch. The project provides modular implementations of popular GAN architectures, including Progressive Growing of GANs (PGAN), DCGAN, and an experimental StyleGAN version. It is built to support both researchers and developers who want to train, evaluate, and extend GANs efficiently across diverse datasets such as CelebA-HQ, FashionGen, DTD,... -
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CQ Games Project
Play a selection of Games including classics and originals!
Play Hangman, Battleships, Snake, a totally original Role-Playing Game (RPG) and Puzzle Games. Certain games can be played against an AI, with two players locally, or with increasing levels of difficulty! This honestly had hundreds of hours of development so i hope you enjoy! Python 3 required to play. -
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TensorNets
High level network definitions with pre-trained weights in TensorFlow
High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 >= TF >= 1.4.0). Applicability. Many people already have their own ML workflows and want to put a new model on their workflows. TensorNets can be easily plugged together because it is designed as simple functional interfaces without custom classes. Manageability. Models are written in tf.contrib.layers, which is lightweight like PyTorch and Keras, and allows for ease of accessibility to every weight and... -
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VGGFace2
VGGFace2 Dataset for Face Recognition
VGGFace2 is a large-scale face recognition dataset developed to support research on facial recognition across variations in pose, age, illumination, and identity. It consists of 3.31 million images covering 9,131 subjects, with an average of over 360 images per subject. The dataset was collected from Google Image Search, ensuring a wide diversity in ethnicity, profession, and real-world conditions. It is split into a training set with 8,631 identities and a test set with 500 identities,... -
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hyperjson
Python module for reading/writing JSON data using Rust's serde-json
A hyper-fast, safe Python module to read and write JSON data. Works as a drop-in replacement for Python's built-in json module. This is alpha software and there will be bugs, so maybe don't deploy to production just yet. -
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Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. -
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PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
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Tail File And Send
Tail some files, change the selection text and send all text selection
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Image Super-Resolution (ISR)
Super-scale your images and run experiments with Residual Dense
...Also, we provide scripts to facilitate training on the cloud with AWS and Nvidia-docker with only a few commands. When training your own model, start with only PSNR loss (50+ epochs, depending on the dataset) and only then introduce GANS and feature loss. This can be controlled by the loss weights argument. The weights used to produce these images are available directly when creating the model object. ISR is compatible with Python 3.6 and is distributed under the Apache 2.0 license.
