Search Results for "machine" - Page 82
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Showing 4715 open source projects for "machine"
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Brain AutoML
Google Brain AutoML
This repository contains a list of AutoML related models and libraries. Google Brain researchers have introduced a new way of programming automated machine learning (AutoML) based on symbolic programming. The researchers also proposed PyGlove, a general symbolic programming library for Python, to implement the symbolic formulation of AutoML. AutoML, designed to fill the machine learning industry’s talent gap, is gaining traction among various organizations. -
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RESTful API Node Server Boilerplate
A boilerplate for building production-ready RESTful APIs using Node.js
A boilerplate/starter project for quickly building RESTful APIs using Node.js, Express, and Mongoose. By running a single command, you will get a production-ready Node.js app installed and fully configured on your machine. The app comes with many built-in features, such as authentication using JWT, request validation, unit and integration tests, continuous integration, docker support, API documentation, pagination, etc. The app has a utility ApiError class to which you can attach a response code and a message, and then throw it from anywhere (catchAsync will catch it). ... -
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earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and generate visual insights without the need for external GIS software by leveraging interactive widgets and mapping libraries. ... -
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Semantic Segmentation in PyTorch
Semantic segmentation models, datasets & losses implemented in PyTorch
Semantic segmentation models, datasets and losses implemented in PyTorch. PyTorch and Torchvision needs to be installed before running the scripts, together with PIL and opencv for data-preprocessing and tqdm for showing the training progress. PyTorch v1.1 is supported (using the new supported tensoboard); can work with earlier versions, but instead of using tensoboard, use tensoboardX. Poly learning rate, where the learning rate is scaled down linearly from the starting value down to zero... -
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React Native Router
The first declarative React Native router
React Native Router is a different API over react-navigation. It helps users to define all the routes in one central place and navigate and communicate between different screens in an easy way. But it also means that react-native-router-flux inherits all limitations and changes from updated versions. v5.0.alpha.x is based on React Navigation v5.x (very early alpha, development in progress, help wanted!). Define all your routes in one React component and navigate from one scene to another... -
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Universal Data Tool
Collaborate & label any type of data, images, text, or documents etc.
...Import from your S3 buckets easily with IAM or Cognito authentication. Working together, we can accomplish more. The Universal Data Tool was built to bring together the best ideas from different machine learning communities. Upload your dataset to Courses to create a training course. Testing and exercises validate that your workforce knows exactly how the data should be labeled. Get started in less than a minute. Courses uses administrator links. No sign up needed. -
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Gluon CV Toolkit
Gluon CV Toolkit
GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection,... -
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Awesome Community Detection Research
A curated list of community detection research papers
A collection of community detection papers. A curated list of community detection research papers with implementations. Similar collections about graph classification, classification/regression tree, fraud detection, and gradient boosting papers with implementations. -
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Self-Attentive Parser
High-accuracy NLP parser with models for 11 languages
LightAutoML is an automated machine learning (AutoML) framework developed by Sberbank AI Lab, designed to facilitate the development of machine learning models with minimal human intervention. -
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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MachineLearningStocks
Using python and scikit-learn to make stock predictions
MachineLearningStocks is a Python-based template project that demonstrates how machine learning can be applied to predicting stock market performance. The project provides a structured workflow that collects financial data, processes features, trains predictive models, and evaluates trading strategies. Using libraries such as pandas and scikit-learn, the repository shows how historical financial indicators can be transformed into machine learning features. -
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Keras TCN
Keras Temporal Convolutional Network
TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the... -
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PORORO
Platform of neural models for natural language processing
pororo performs Natural Language Processing and Speech-related tasks. It is easy to solve various subtasks in the natural language and speech processing field by simply passing the task name. Recognized speech sentences using the trained model. Currently English, Korean and Chinese support. Get vector or find similar words and entities from pretrained model using Wikipedia. -
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Bayesian machine learning notebooks
Notebooks about Bayesian methods for machine learning
Notebooks about Bayesian methods for machine learning. -
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LoLCode1337 (speak lolcode leet) is an implementation of the esoteric programming language lolcode. It offers a compiler, virtual machine (=interpreter), debugger, internal editor and it's commands set is close to that what other lolcode implementations offer. More to come soon.
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git-notify
Communicate important updates to your team via git commit messages
...In a small team, a Slack message works okay, but in larger teams and distributed organizations (such as open-source projects), reaching everyone can be a pain. git-notify allows you to embed announcements into your git commit messages. And display them to another developer on a machine, far far away. Just add "git-notify:" to your git commit message, and anything that follows will be displayed when another developer pulls that commit, or switches from a branch that does not contain that commit to one that does. If you're using a merge or squash commit strategy on GitHub, you can also add them to the extended commit message when landing a PR. git-notify will display a message for every "git-notify:" prefix it finds in the commit log that was just pulled/merged/rebased/checked out. -
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Mininet
Emulator for rapid prototyping of Software Defined Networks
Mininet creates a realistic virtual network, running real kernel, switch and application code, on a single machine (VM, cloud or native), in seconds, with a single command. Because you can easily interact with your network using the Mininet CLI (and API), customize it, share it with others, or deploy it on real hardware, Mininet is useful for development, teaching, and research. Mininet is also a great way to develop, share, and experiment with Software-Defined Networking (SDN) systems using OpenFlow and P4. ... -
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BerryNet
Deep learning gateway on Raspberry Pi and other edge devices
This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events... -
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wrk
Modern HTTP benchmarking tool
...An optional LuaJIT script can perform HTTP request generation, response processing, and custom reporting. Details are available in SCRIPTING and several examples are located in scripts. The machine running wrk must have a sufficient number of ephemeral ports available and closed sockets should be recycled quickly. To handle the initial connection burst the server's listen(2) backlog should be greater than the number of concurrent connections being tested. -
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Data Science Notes
Curated collection of data science learning materials
Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. Because it aggregates topics in one place, learners can move linearly or jump into specific areas as needed during projects. The notes also highlight common pitfalls and good practices, which helps beginners adopt professional habits early. ... -
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Photoshop CC Linux
Photoshop CC v19 installer for Gnu/Linux
This bash script helps you to install Photoshop CC version 19 on your Linux machine using wine behind the scene and sets some necessary components up for the best performance. Downloads necessary components and installs them (vcrun, atmlib, msxml...). Downloads photoshop.exe installer. Creates photoshop command and a desktop entry. Wine dark mode. Supports graphic cards like (intel, Nvidia). Saves the downloaded files in your cache directory. -
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This Matlab code is used for demonstration of the effect of CDF-TS as a preprocessing method to transform data. Written by Ye Zhu, Deakin University, April 2021, version 1.0. This software is under GNU General Public License version 3.0 (GPLv3) This code is a demo of method described by the following publication: Zhu, Y., Ting, K.M., Carman, M. and Angelova, M., 2021, April. CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities. Pattern...
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Ansible Config Management Database
Generate host overview from ansible fact gathering output
...It supports multiple types of output (HTML, CSV, SQL, etc) and extends information gathered by Ansible with custom data. For each host, it also shows the groups, host variables, custom variables and machine-local facts. Some templates, such as txt_table and html_fancy, support columns. If a template supports columns, you can use the --columns / -c command-line option to specify which columns to show. The --columns take a comma-separated list of columns (no spaces!) which should be shown. The columns must be specified by their id field. ... -
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BudgetML
Deploy a ML inference service on a budget in 10 lines of code
Deploy a ML inference service on a budget in less than 10 lines of code. BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST,... -
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imeight
The imaginary eight-bit machine
Try-it page: https://imeight.sourceforge.io/ (development environment, which is not mobile friendly) An HTML5 emulator of a machine that never existed. The emulator brings back memories from the 1980s, offers graphical features like sprites, character generator, 16-color palette. One goal is to create a framework for making games with 8-bit look and feel, including the process of programming. The programming tutorial helps beginners enter the world of programming in a gamified way. -
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TTS
Deep learning for text to speech
TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed, and quality. TTS comes with pre-trained models, tools for measuring dataset quality, and is already used in 20+ languages for products and research projects. Released models in PyTorch, Tensorflow and TFLite. Tools to curate Text2Speech datasets underdataset_analysis. Demo server for model testing. Notebooks for extensive model...
