Search Results for "python code editor" - Page 6
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Showing 183 open source projects for "python code editor"
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Optimized Storage for temporal Data
open Optimized Storage of time series data
Beta version. Base class for optimized storage of time series data. Uses any kind of relational database. Cross plateform with multiple languages (C++, C#, Java). Conditional storage based on value variation : DeltaValue and DeltaTime params. Get back data without losts. -
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transformer
A TensorFlow Implementation of the Transformer
Transformer is a TensorFlow implementation of the architecture introduced in the Attention Is All You Need paper. It was created as a readable and relatively modular reference for understanding and experimenting with Transformer-based machine translation. The updated implementation corrects issues involving masking, positional encoding, and other parts of the original code. It adds components such as byte-pair encoding and shared weight matrices. Training and evaluation are demonstrated with... -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with... -
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captcha_break
Identification codes
This project will use Keras to build a deep convolutional neural network to identify the captcha verification code. It is recommended to use a graphics card to run the project. The following visualization codes are jupyter notebookall done in . If you want to write a python script, you can run it normally with a little modification. Of course, you can also remove these visualization codes. captcha is a library written in python to generate verification codes. ... -
Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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pytorch-examples
Simple examples to introduce PyTorch
The pytorch-examples project is a collection of concise and practical examples demonstrating how to use PyTorch for machine learning and deep learning tasks. It focuses on clarity and minimalism, providing small, self-contained scripts that illustrate key concepts such as neural network training, optimization, and data handling. The examples cover a range of topics including supervised learning, generative models, and reinforcement learning, making it a valuable resource for both beginners... -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This... -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
...Advanced sections touch on neural networks and distributed computing topics, helping you bridge from basics to production-adjacent workflows. The collection is suitable for self-paced study, quick reference, or as teaching materials in workshops. By combining narrative explanations with executable code, it shortens the path from theory to working prototypes. -
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Autologging
Easier logging and tracing of Python functions and class methods.
Autologging eliminates boilerplate logging setup code and tracing code, and provides a means to separate application logging from program flow and data tracing. Autologging provides two decorators and a custom log level: "autologging.logged" decorates a class to create a __log member. By default, the logger is named for the class's containing module and name (e.g. "my.module.ClassName"). -
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WIP
Create Siri Shortcuts with Python
python-shortcuts is a library to create Siri Shortcuts on your laptop with your favorite text editor. It uses toml to represent shortcuts. The library is in a very early development state (PR welcome!), so it does not support all actions from the Shortcuts app. -
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FilterPy
Python Kalman filtering and optimal estimation library
FilterPy is a Python library for Kalman filtering and related state-estimation methods. It implements standard, extended, and unscented Kalman filters, along with Kalman smoothers. The package also includes particle filters, least-squares filters, fading-memory filters, g-h filters, discrete Bayes methods, and H-infinity tools. Its code favors readability and close correspondence with the underlying equations. -
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SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with... -
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Skater
Python library for model interpretation/explanations
...The library has embraced object-oriented and functional programming paradigms as deemed necessary to provide scalability and concurrency while keeping code brevity in mind. -
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Python/xarray tutorial
Python/xarray tutorial for GEOS-Chem users
If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. To best way to get the scientific Python environment is using the Conda management system. ... -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution... -
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Compare GAN
Compare GAN code
compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. With... -
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AlfredWorkflow.com
A public Collection of Alfred Workflows
AlfredWorkflow.com is a public collection of workflows created for Alfred 2 on macOS. It was designed to help users search, install, share, and discover automations without building each workflow from scratch. The repository contains hundreds of downloadable workflows alongside source code that developers can study. A Workflow Searcher lets users query the collection directly from Alfred. The project also exposes workflow metadata through a JSON API for programmatic access. GitHub-hosted... -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. Because it aggregates... -
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Assorted projects. General-purpose libraries for Python, C++, Scala, bash, and others. Meta-programming tools. System utilities. UI components. Web APIs. Configuration files. Benchmarks. Programming competition entries. And much more.
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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Pyrlang
Erlang node implemented in Python 3.5+ (Asyncio-based)
This is a drop-in Erlang node implementation in Python 3, implementing a network Erlang node protocol. It was designed to allow interoperation between existing Python projects and BEAM languages: Erlang, Elixir, Gleam, Luaerl, LFE, Clojerl, and such. With just a few lines of startup code your Python program becomes an Erlang network node, participating in the Erlang cluster. -
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Flasky
Companion code to my O'Reilly book "Flask Web Development"
Flasky is a comprehensive example web application built with the Flask microframework that demonstrates best practices for developing real-world Python web applications, covering everything from project structure and configuration to database models, authentication, and deployment. It serves as both a tutorial and sample codebase that walks developers through building a full-featured web application, including user registration and login, role-based permissions, user profiles, and content... -
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neovim-remote
This package provides an executable called nvr
neovim-remote is a command-line tool that lets users control existing Neovim processes from the shell. It provides an executable called nvr, which supports remote file opening, command execution, key sending, and expression evaluation. The tool solves a common terminal workflow problem by opening files inside an already running Neovim session instead of starting nested editor instances. It can be used from shell commands, terminal buffers, scripts, and Git editor workflows. If no target... -
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TensorFlow World
Simple and ready-to-use tutorials for TensorFlow
This repository aims to provide simple and ready-to-use tutorials for TensorFlow. The explanations are present in the wiki associated with this repository. There are different motivations for this open source project. TensorFlow (as we write this document) is one of / the best deep learning frameworks available. The question that should be asked is why has this repository been created when there are so many other tutorials about TensorFlow available on the web? Deep Learning is in very high... -
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Icon Font to PNG
Python script (and library) for exporting icons from icon fonts
...You can use IconFont (and IconFontDownloader for that matter) directly inside your Python project. There's no proper documentation as of now, but the code is commented and should be pretty straightforward to use. -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction....
