Search Results for "machine" - Page 9
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Showing 4715 open source projects for "machine"
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APKiD
Android Application Identifier for Packers, Protectors and Obfuscators
APKiD gives you information about how an APK was made. It identifies many compilers, packers, obfuscators, and other weird stuff. It's PEiD for Android. -
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AutoMLPipeline.jl
Package that makes it trivial to create and evaluate machine learning
...It leverages on the built-in macro programming features of Julia to symbolically process, and manipulate pipeline expressions and makes it easy to discover optimal structures for machine learning regression and classification. To illustrate, here is a pipeline expression and evaluation of a typical machine learning workflow that extracts numerical features (numf) for ica (Independent Component Analysis) and pca (Principal Component Analysis) transformations, respectively, concatenated with the hot-bit encoding (ohe) of categorical features (catf) of a given data for rf (Random Forest) modeling. -
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Spring Statemachine
Framework for application developers to use state machine concepts
The Spring Statemachine project aims to provide a common infrastructure to work with state machine concepts in Spring applications. It is advised to check the actual state of this project by referring to the latest releases found on the Spring Statemachine Project Page. The git repo default branch may be relatively unstable when new features are added to the source code. Spring Statemachine uses a Gradle-based build system. In the instructions below, . -
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Deep Java Library (DJL)
An engine-agnostic deep learning framework in Java
...DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides native Java development experience and functions like any other regular Java library. You don't have to be a machine learning/deep learning expert to get started. You can use your existing Java expertise as an on-ramp to learn and use machine learning and deep learning. You can use your favorite IDE to build, train, and deploy your models. DJL makes it easy to integrate these models with your Java applications. Because DJL is deep learning engine agnostic, you don't have to make a choice between engines when creating your projects. ... -
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TikZ
TikZ figures for concepts in physics/chemistry/ML
Collection of 111 standalone TikZ figures for illustrating concepts in physics, chemistry, and machine learning. Check out janosh.github.io to search, sort, open in Overleaf, and download figures (PDF/SVG/PNG) from this collection. -
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FLAML
A fast library for AutoML and tuning
FLAML is a lightweight Python library that finds accurate machine learning models automatically, efficiently and economically. It frees users from selecting learners and hyperparameters for each learner. For common machine learning tasks like classification and regression, it quickly finds quality models for user-provided data with low computational resources. It supports both classical machine learning models and deep neural networks. -
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PlexGuide.com
Rapidly deploy multiple-hasty Docker containers
...PGBlitz utilizes Ansible and Docker to streamline your Media Server while deploying multiple tools for your Server Operations. Deploys multiple programs/apps and functional within 10 - 30 seconds. Deploy PlexGuide on a remote machine, local machine, VPS, or virtual machine. Deploy PlexGuide utilizing Google's GSuite for unlimited space or through the solo or multiple HD editions. Deploys a Reverse Proxy (Traefik) so you can obtain https certificates on all your containers. Backup and Restore data through your Google Drive. Aligns data and ports for efficiency. ... -
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Cog
Package and deploy machine learning models using Docker containers
...Cog also resolves compatibility issues between frameworks and GPU libraries by automatically selecting compatible combinations of CUDA, cuDNN, and machine learning frameworks such as PyTorch or TensorFlow. Cog automatically generates a RESTful HTTP API for running predictions, enabling models to be accessed programmatically through a built-in prediction server. -
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Valet Linux
A fork of Laravel Valet to work in Linux.
...You can even share your sites publicly using local tunnels. Yeah, we like it too. Valet Linux configures your system to always run Nginx in the background when your machine starts. Then, using DnsMasq, Valet proxies all requests on the *.test domain to point to sites installed on your local machine. In other words, a blazing-fast Laravel development environment that uses roughly 7MB of RAM. Valet Linux isn't a complete replacement for Vagrant or Homestead but provides a great alternative if you want flexible basics, prefer extreme speed, or are working on a machine with a limited amount of RAM. -
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Laravel Valet
A more enjoyable local development experience for Mac
...You can even share your sites publicly using local tunnels. Yeah, we like it too. Laravel Valet configures your Mac to always run Nginx in the background when your machine starts. Then, using DnsMasq, Valet proxies all requests on the *.test domain to point to sites installed on your local machine. In other words, a blazing-fast Laravel development environment that uses roughly 7 MB of RAM. Valet isn't a complete replacement for Vagrant or Homestead, but provides a great alternative if you want flexible basics, prefer extreme speed, or are working on a machine with a limited amount of RAM. -
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PyGAD
Source code of PyGAD, Python 3 library for building genetic algorithms
PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function. -
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Fengari
The Lua VM written in JS ES6 for Node and the browser
The Lua VM written in JS ES6 for Node and the browser. This repository contains the core Fengari code (which is a port of the Lua C library) which includes parser, virtual machine, and base libraries. However, it is rare to use this repository directly. -
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MinIO
High performance object storage server compatible with Amazon S3 APIs
MinIO is a high performance object storage server that is API compatible with Amazon S3 cloud storage service. MinIO makes it easy to build high performance, cloud native data infrastructure for machine learning, analytics and application data workloads. It is incredibly fast, enabling object storage to operate as the primary storage tier for a diverse set of workloads. It is also built to be cloud native and enterprise ready. MinIO is being used worldwide in various production deployments, and is leading the way as the most downloaded object storage server in the industry. -
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MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
...We developed a desktop application called MLJAR Studio. It is a notebook-based development environment with interactive code recipes and a managed Python environment. All running locally on your machine. We are waiting for your feedback. The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist. It abstracts the common way to preprocess the data, construct the machine learning models, and perform hyper-parameter tuning to find the best model. ... -
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BindsNET
Simulation of spiking neural networks (SNNs) using PyTorch
A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch Tensor functionality. BindsNET is a spiking neural network simulation library geared towards the development of biologically inspired algorithms for machine learning. This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the Biologically Inspired Neural & Dynamical Systems (BINDS) lab. -
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ml.js
Machine learning tools in JavaScript
This library is a compilation of the tools developed in the mljs organization. It is mainly maintained for use in the browser. If you are working with Node.js, you might prefer to add to your dependencies only the libraries that you need, as they are usually published to npm more often. We prefix all our npm package names with ml- (eg. ml-matrix) so they are easy to find. -
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Ray
A unified framework for scalable computing
...Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework. Scale reinforcement learning (RL) with RLlib, a framework-agnostic RL library that ships with 30+ cutting-edge RL algorithms including A3C, DQN, and PPO. Easily build out scalable, distributed systems in Python with simple and composable primitives in Ray Core. -
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Meetily
Privacy first, AI meeting assistant with 4x faster Parakeet/Whisper
This project is a privacy-first AI meeting assistant that captures meeting audio, produces real-time transcripts, and generates summaries while keeping processing entirely on your own machine or infrastructure. It’s built for organizations that want meeting intelligence without sending recordings or transcripts to third-party cloud services, which helps address compliance and data sovereignty requirements. The app supports live transcription with local model options (including Whisper- and Parakeet-based workflows) and presents the transcript as the meeting happens, making it useful both for note-taking and accessibility. ... -
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Tensorforce
A TensorFlow library for applied reinforcement learning
Tensorforce is an open-source deep reinforcement learning framework built on TensorFlow, emphasizing modularized design and straightforward usability for applied research and practice. -
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Lumen Framework
The Laravel Lumen Framework
...Lumen attempts to take the pain out of development by easing common tasks used in the majority of web projects, such as routing, database abstraction, queueing, and caching. The Lumen framework has a few system requirements. Of course, all of these requirements are satisfied by the Laravel Homestead virtual machine, so it's highly recommended that you use Homestead as your local Lumen development environment. Lumen utilizes Composer to manage its dependencies. So, before using Lumen, make sure you have Composer installed on your machine. Since Lumen is a totally separate framework from Laravel, it does not intentionally offer compatibility with any additional Laravel libraries like Cashier, Passport, Scout, etc. -
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TensorFlow Model Optimization Toolkit
A toolkit to optimize ML models for deployment for Keras & TensorFlow
The TensorFlow Model Optimization Toolkit is a suite of tools for optimizing ML models for deployment and execution. Among many uses, the toolkit supports techniques used to reduce latency and inference costs for cloud and edge devices (e.g. mobile, IoT). Deploy models to edge devices with restrictions on processing, memory, power consumption, network usage, and model storage space. Enable execution on and optimize for existing hardware or new special purpose accelerators. Choose the model... -
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HackTheBox CTF Writeups
This cheasheet is aimed at the CTF Players and Beginners
...It is designed to help CTF players and cybersecurity learners study complete penetration-testing scenarios in legal practice environments. Entries are organized by machine name and include the target operating system and difficulty level. The collection spans Linux, Windows, FreeBSD, Solaris, and other environments across easy through insane difficulty ratings. Each machine links to a detailed Hacking Articles writeup explaining the associated challenge. The broad catalog lets learners choose labs that match their current skill level or preferred platform. ... -
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Sonic Agent
Agent of Sonic cloud real machine platform
Agent of Sonic Cloud Real Machine Platform. Sonic is a platform that integrates remote control debugging and automated testing of mobile devices, and strives to create a better use experience for global developers and test engineers. -
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DeepXDE
A library for scientific machine learning & physics-informed learning
DeepXDE is a library for scientific machine learning and physics-informed learning. DeepXDE includes the following algorithms. Physics-informed neural network (PINN). Solving different problems. Solving forward/inverse ordinary/partial differential equations (ODEs/PDEs) [SIAM Rev.] Solving forward/inverse integro-differential equations (IDEs) [SIAM Rev.] fPINN: solving forward/inverse fractional PDEs (fPDEs) [SIAM J. -
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SHAP
A game theoretic approach to explain the output of ml models
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions. While SHAP can explain the output of any machine learning model, we have developed a high-speed exact algorithm for tree ensemble methods. Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark tree models. ...
