Search Results for "machine" - Page 28
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Showing 1802 open source projects for "machine"
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Euler
A distributed graph deep learning framework.
As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable... -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and compare the results. ... -
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NanoVM - a portable tiny java vm running on microcontrollers with at least 8k code space, especially Atmel AVR controllers. Robotic examples for the Asuro, the c't-Bot and the Nibo robot are included.
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Serial Console (sc)
Minimal terminal program to get access to a serial console
serialconsole (sc) is a minimal terminal program allowing to use one machine to access the serial console of another machine. -
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PyCBC
Learn how to use PyCBC to analyze gravitational-wave data
...Many of these tutorials will require you to make edits to config files as part of their exercises. At the moment this isn't easy to do on services like Google Colab. However, you can do them either on your local machine or by using services such as mybinder or sciserver which allow a full juypterhub experience with the ability to view and edit text files. Below we give links to the tutorials that should directly work in Google Colab, however. -
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Keystone Engine
Keystone assembler framework: Core (Arm, Arm64, Hexagon, Mips, etc.)
Keystone is a lightweight multi-platform, multi-architecture assembler framework. Multi-architecture, with support for Arm, Arm64 (AArch64/Armv8), Ethereum Virtual Machine, Hexagon, Mips, PowerPC, Sparc, SystemZ, & X86 (include 16/32/64bit). Clean/simple/lightweight/intuitive architecture-neutral API. Implemented in C/C++ languages, with bindings for Java, Masm, Visual Basic, C#, PowerShell, Perl, Python, NodeJS, Ruby, Go, Rust, Haskell & OCaml available. Native support for Windows & *nix (with Mac OSX, Linux, *BSD & Solaris confirmed). ... -
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SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. -
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ocapi
C-level driver collection for MSP430 and derivatives
...So it should work, no matter if you live in the Windows, Linux or Mac world. 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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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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VM Migration Assistant
Virtual Disk Convert Between VMDK,VHD(X),VDI,QCOW/QCOW2,RAW(IMG)
...For saving time during migration and hypervisor switch, V2V Converter / P2V Migrator enables to convert VMs directly from one hypervisor storage to another, without creating an extra VM disk copy. On top of that, the utility ensures a safe P2V migration by using a VSS snapshot of the source machine to ensure data consistency. -
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End-To-End
End-To-End is a crypto library to encrypt, decrypt, digital sign
End-to-End was a client-side encryption project that prototyped OpenPGP-compatible, end-to-end encrypted messaging in the browser. The idea was to move cryptographic operations entirely to the user’s machine—key generation, encryption, and signature—so messages remain unreadable to intermediaries. It packaged a JavaScript crypto library, UI elements, and a browser extension workflow that could integrate with webmail-style UIs without server changes. The codebase emphasized careful key handling, usability experiments around key discovery and verification, and mitigations against common web threats like XSS. ... -
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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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Simplify
Android virtual machine and deobfuscator
Simplify virtually executes an app to understand its behavior and then tries to optimize the code so that it behaves identically but is easier for a human to understand. Each optimization type is simple and generic, so it doesn't matter what specific type of obfuscation is used. Provides a virtual machine sandbox for executing Dalvik methods. After executing a method, it returns a graph containing all possible register and class values for every execution path. It works even if some values are unknown, such as file and network I/O. For example, any if or switch conditional with an unknown value results in both branches being taken. ... -
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Multrin
Organize apps windows in tabs like in abandoned Windows Sets and more
...Multrin works currently only on Windows and macOS. Support for Linux coming soon. Before running Multrin in development mode, please ensure you have Node.js installed on your machine. When running on Windows, make sure you have build tools installed. You can install them by running as an administrator. -
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IntrOS
Free cooperative operating system designed for microcontrollers
Free, simple and tiny cooperative operating system (OS) designed for deeply embedded applications. Target: ARM Cortex-M, STM8, AVR8. It was inspired by the concept of a state machine. Procedure executed by the task (task state) doesn't have to be noreturn-type. It will be executed into an infinite loop. There's a dedicated function for immediate change the task state. -
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StateOS
Free real-time operating system designed for microcontrollers
Free, extremely simple, amazingly tiny and very fast real-time operating system (RTOS) designed for deeply embedded applications. Target: ARM Cortex-M, STM8. It was inspired by the concept of a state machine. Procedure executed by the task (task state) doesn't have to be noreturn-type. It will be executed into an infinite loop. There's a dedicated function for immediate change the task state. -
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Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
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GuillotineMenu.swift
Our Guillotine Menu Transitioning Animation implemented in Swift
Our Guillotine Menu Transitioning Animation implemented in Swift reminds a bit of a notorious killing machine. Now, it's for you to decide, should or not your menu drop from top left corner of the screen or from your navigation bar, because if you want animation like in the example, you must make your menu view controller conform to "GuillotineMenu" protocol. When you confirm to this protocol, you must make a menu button and title, you don't need to make a frame for them, because the animator will make it itself. ... -
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TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the... -
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Shipit
Universal automation and deployment tool
...If you can't call shipit.initConfig(...) right away because you need to get data asynchronously to do so, you can return a promise from the module. List of files excluded in copyFromRemote or copyToRemote methods. Allows you to ‘become’ another user, different from the user that logged into the machine (remote user). If shallowClone is set to false, this directory will be used to clone the repository before deploying it. -
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The Neural Process Family
This repository contains notebook implementations
Neural Processes (NPs) is a collection of interactive Jupyter/Colab notebook implementations developed by Google DeepMind, showcasing three foundational probabilistic machine learning models: Conditional Neural Processes (CNPs), Neural Processes (NPs), and Attentive Neural Processes (ANPs). These models combine the strengths of neural networks and stochastic processes, allowing for flexible function approximation with uncertainty estimation. They can learn distributions over functions from data and efficiently make predictions at new inputs with calibrated uncertainty — making them useful for few-shot learning, Bayesian regression, and meta-learning. ... -
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CrypTen
A framework for Privacy Preserving Machine Learning
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic differentiation and neural network operations. ... -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments... -
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Lucet
Lucet, the Sandboxing WebAssembly Compiler.
Lucet is a native WebAssembly compiler and runtime designed to securely execute untrusted code with high performance and strong isolation guarantees. Developed by the Bytecode Alliance, it focuses on ahead-of-time compilation, converting WebAssembly modules into native machine code before execution to achieve fast startup times and predictable performance. Lucet is particularly notable for its use in edge computing environments, where low latency and efficient resource usage are critical, such as in content delivery networks. It leverages the Cranelift code generator to produce optimized native binaries and provides a runtime that enforces strict sandboxing, ensuring that untrusted code cannot compromise the host system. ... -
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TypeScript Koa Starter
TypeScript Koa Starter
Koa with TypeScript's application generator. Creates a new typescript koa application. application is configured to use TypeScript instead of plain JavaScript. Node Js is great for the rapid development of web-projects, but is often neglected because of the lack of type safety. TypeScript solves this issue and (along with its linter file) can even make your code more robust than some other static languages like Java.
