Search Results for "machine" - Page 23
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Showing 1802 open source projects for "machine"
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GFPGAN
GFPGAN aims at developing Practical Algorithms
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. Colab Demo for GFPGAN; (Another Colab Demo for the original paper model) Online demo: Huggingface (return only the cropped face) Online demo: Replicate.ai (may need to sign in, return the whole image). Online demo: Baseten.co (backed by GPU, returns the whole image). We provide a clean version of GFPGAN, which can run without CUDA extensions. So that it can run in Windows or on CPU mode. GFPGAN aims at developing... -
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Gym
Toolkit for developing and comparing reinforcement learning algorithms
Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no... -
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ml-surveys
Survey papers summarizing advances in deep learning, NLP, CV, graphs
The ml-surveys repository is a broad, maintainable overview of survey papers across many subfields of machine learning — including deep learning, NLP, computer vision, graph ML, reinforcement learning, recommendation systems, embeddings, meta-learning, and more. Instead of diving into code or experiments, this repo gathers authoritative survey and review articles, summarizing the state-of-the-art, trends, challenges, and directions within each subdomain. -
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Amazon SageMaker Operators Kubernetes
Amazon SageMaker operator for Kubernetes
Amazon SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. -
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DuranDuranbot
Teachable/trainable artificially intelligent music bot
A teachable/trainable artificially intelligent music bot fundamentally inspired by how the new wave band Duran Duran composes music. This program utilizes many algorithmic/AI techniques/processes, including machine learning; which allow you to teach/train it to compose music which you prefer... and the technique which is the foundation of the design of DuranDuranbot, which was directly inspired by how Duran Duran writes music........ Called, "bit by bit circular composition"....... and it's explanation can be found here - https://scsynth.org/t/bit-by-bit-circular-composition/1107 This program is written in the SuperCollider programming language - https://en.wikipedia.org/wiki/SuperCollider Contact - ken_brant@ymail.com -
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BEVFormer
Implementation of BEVFormer, a camera-only framework
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV... -
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Windows Dev Box Setup Scripts
Scripts to simplify setting up a Windows developer box
Windows Dev Box Setup Scripts is a Microsoft-maintained collection of PowerShell “recipes” and helper scripts that automate and streamline provisioning a Windows developer workstation for many common stacks (desktop .NET/C++, web/Node, machine learning, DevOps, containers, and more). The project uses Chocolatey and Boxstarter under the hood and exposes one-click Boxstarter links and standalone scripts so you can boot a machine, install SDKs, runtimes, tooling, and manage reboots unattended. Scripts are organized as high-level recipes (for example: Full Desktop App, Web, Web + NodeJS, Machine Learning, DevOps/Azure) which call smaller helper scripts stored in a scripts/ folder so recipes stay readable and easy to customize. ... -
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Inform
The core software distribution for the Inform 7 programming language
...The language is distinctive for its natural-language-inspired syntax that reads almost like English, allowing storytellers to define rooms, objects, characters, and narrative logic in an intuitive way that emphasizes expressive clarity and literary structure. When you write in Inform, the source code is compiled into playable story files that run on interactive fiction virtual machines such as Z-machine or Glulx, enabling classic text-based gameplay with modern tooling. Inform handles the underlying complexities of text parsing, world modeling, state management, and player input, so authors can focus on narrative design rather than low-level engine details. -
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q
Developer's programmable text & binary editor
Mostly WYSIWYG command-line driven editor with editable commands, a powerful macro facility including a stack architecture run machine, macro debugger, online help, a foundation macro set and extension macro sets for C, python, Ada and Tcl development and email composition. Q tries to resolve the old tabs vs spaces conundrum: e.g. in Linux source, the user can automatically enforce leading tabs, no space-before-tab leading sequences and no trailing spaces. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Hacker Scripts
Based on a true story
...The repository gathers playful utilities (originally shell and Ruby scripts) that automate short, real-world tasks — for example, sending a quick “late at work” text when SSH sessions are active, firing off an automated “I’m sick / working from home” email on certain mornings, or even talking to a networked coffee machine to start brewing at precisely the right moment. The README explains the origin story and highlights several canonical scripts and provides usage notes such as required environment variables and cron examples for scheduling. Contributors have provided implementations and ports in many languages and folders (shell, Ruby, Python, Node, Perl, PowerShell, Go, Java, etc.), and the project explicitly welcomes pull requests that add additional language implementations. -
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MELO
Machine Executable Language Ontology (MELO)
This project is intended to fill the gap between the semantic web and the mainstream of software engineering, especially to integrate the semantic web with programming languages, and find an ontological representation of programming languages, including abstract syntax code execution, and global interoperability in execution environments. The machine executable language is modelled in OWL 2 DL using OWL API in C++ developed in this project. -
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PyTorch Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.
TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please... -
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Buck
Build system that encourages the creation of small, reusable modules
...It encourages the creation of small, reusable modules consisting of code and resources, and supports a variety of languages on many platforms. Buck builds independent artifacts in parallel to take advantage of multiple cores on your machine. Further, it reduces incremental build times by keeping track of unchanged modules so that the minimal set of modules is rebuilt. Buck only uses the declared inputs, which means everybody gets the same results. Buck looks at the contents of your inputs, not their timestamps to figure out what needs to be built. As a result, incremental builds should always be correct, so there's no need to perform a clean build. ... -
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Lingua
The most accurate natural language detection library for Java
Its task is simple: It tells you which language some provided textual data is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. -
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Termshark
A terminal UI for tshark, inspired by Wireshark
A terminal user-interface for tshark, inspired by Wireshark. If you're debugging on a remote machine with a large pcap and no desire to scp it back to your desktop, termshark can help! Read pcap files or sniff live interfaces (where tshark is permitted). Filter pcaps or live captures using Wireshark's display filters. Reassemble and inspect TCP and UDP flows. View network conversations by protocol. Copy ranges of packets to the clipboard from the terminal. -
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Julia.jl
Curated decibans of Julia programming language
Julia.jl is a curated collection of knowledge resources for the Julia programming language, designed to support high-performance numerical analysis and computational science. The repository aggregates diverse content across domains such as mathematics, physics, data science, optimization, machine learning, and supercomputing. It functions as a structured index, helping developers, researchers, and learners easily find materials to deepen their understanding of Julia’s ecosystem. The project emphasizes community contributions, encouraging users to expand and refine the resource pool. With a wide range of topic-focused documents, it provides both academic and practical references for applied research and development. ... -
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a... -
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Pegasus5
New OOPs Language
This project is to create a fully working implementation of the Pegasus source language. Pegasus will be implemented in C and will compile to native machine code. It is hoped that the system will be an improvement on Java. The number of members implementing this project will be limited. Once the project is complete we hope to create applications in Pegasus and compile them to run on any platform that supports the C language. We could even write a Console Request Interface in Pegasus. -
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X11-Basic
A BASIC interpreter and compiler with graphics.
X11-Basic is a dialect of the BASIC programming language with graphics capability that integrates features like shell scripting, cgi-Programming and full graphical visualisation into the easy to learn basic language on modern computers. -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the... -
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SC/MP Processor Emulator
Emulator of the ancient 8 bit microprocessor SC/MP 2
Emulator of the ancient 8 bit microprocessor ISP-8A 500D/600D or more common "SC/MP" from National Semiconductor. The download contains all sources plus an executable Java Jar file to start right away. Some SC/MP hex dump examples are provided in directory "/etc" as well. The download also contains unit tests and some helping documentation (also in /etc). You may slow down the CPU operations, displaying the CPUs status register as LEDs, to watch the CPU working with its... -
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Flashlight library
A C++ standalone library for machine learning
Flashlight is a fast, flexible machine learning library written entirely in C++ by Facebook AI Research and the creators of Torch, TensorFlow, Eigen, and Deep Speech. Native support in C++ and simple extensibility make Flashlight a powerful research framework that's hackable to its core and enables fast iteration on new experimental setups and algorithms with little unopinionated and without sacrificing performance. -
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SageMaker MXNet Inference Toolkit
Toolkit for allowing inference and serving with MXNet in SageMaker
...Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. -
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pyTorch Tutorials
Build your neural network easy and fast
...The project is structured around clear, executable Python scripts and Jupyter notebooks that demonstrate regression, classification, convolutional networks, recurrent networks, autoencoders, and generative adversarial networks, which gives learners practical exposure to real machine learning tasks. Each example explains PyTorch’s dynamic computation graph, optimization techniques, and core abstractions in a way that is accessible and reproducible. Contributors and authors integrate visual and coded examples so readers can see both the theory and the implementation side-by-side. -
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WFIO Java Bindings
Java bindings for WFIO
This subproject contains a parallel implementation effort for the Java Virtual Machine. It allows for you to use the WFIO interface in your Java applications and will include a translation layer so that you can talk to the native WFIO libraries. This subproject exists partially to overcome the 8.3 file naming convention that WFIO itself is limited to.
