Search Results for "get"
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Showing 11 open source projects for "get"
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ThingPulse ESP8266 Weather Station
ESP8266 Weather Station library supporting OpenWeatherMap
This code works best with the NodeMCU V2 ESP8266 module and an 0.96" OLED display. To get you up and running in no time we created a kit that contains all the necessary parts. By buying this and other kits from us you are funding the maintenance and development of this library. Make sure you use a version of the Arduino IDE which is supported by the ESP8266 platform. If you are using the PlatformIO environment for building, choose one of the available IDE integration or the Atom-based IDE, install libraries 561, 562, and 563 with "platformio lib install", adapt the WeatherStationDemo.ino file to your needs. ... -
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AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run... -
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Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. Catalyst is compatible with Python 3.6+. ... -
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covid19model
Code for modelling estimated deaths and cases for COVID19
...The code should be run in full mode to obtain credible results. Not running a full run to estimate anything is not recommended and discouraged. Only a full run should be used to get results. -
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Lucid
A collection of infrastructure and tools for research
Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs... -
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Data Science at the Command Line
Data science at the command line
...This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools, useful whether you work with Windows, macOS, or Linux. You’ll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you’re comfortable processing data with Python or R, you’ll learn how to greatly improve your data science workflow by leveraging the command line’s power. -
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NiftyNet
An open-source convolutional neural networks platform for research
...NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging data. Quickly build new solutions to your own image analysis problems. NiftyNet currently supports medical image segmentation and generative adversarial networks. NiftyNet is not intended for clinical use. -
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google-play-scraper
Node.js scraper to get data from Google Play
Node.js module to scrape application data from the Google Play store. Retrieves the full detail of an application. Retrieves a list of applications from one of the collections at Google Play. Retrieves a list of apps that results of searching by the given term. Returns the list of applications by the given developer name. Given a string returns up to five suggestions to complete a search query term. Retrieves a page of reviews for a specific application. Returns a list of similar apps to the... -
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BLEU (Body Language Effect on Users)
Body Language Effect on Users
...As you can see in my GPE documentation, I no longer use the friend keyword quite so liberally (In fact, haven't used it once in GPE). The naming convention I have used is a bit wonky as well. In addition the scoping for all the variables, methods, etc. really needs to be reorganized. I might get around to doing a refactoring on this code, but I wouldn't hold my breath. I wrote it over three years ago, and wrote it in quite a hurry when I did. If you compare this stuff with my GPE code, its like night and day. Well, hopefully somebody learning to work with OGRE or to program in C++, might find it useful -
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Mac upgraded to OSX, Lepard which do not support os9 anymore. This project is build to help DNA Strider user to get their data out and perform some basic DNA analyze function.
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