Search Results for "python windows" - Page 72
Sort By:
Showing 16864 open source projects for "python windows"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
1
Modeltranslation
Translates Django models using a registration approach
The modeltranslation application is used to translate dynamic content of existing Django models to an arbitrary number of languages without having to change the original model classes. It uses a registration approach (comparable to Django's admin app) to be able to add translations to existing or new projects and is fully integrated into the Django admin backend. The advantage of a registration approach is the ability to add translations to models on a per-app basis. You can use the same app... -
2
django-admin-interface
Django's default admin interface made customizable
django-admin-interface is a modern responsive flat admin interface customizable by the admin itself. Themes management and customization (you can customize admin title, logo and colors) You can add a theme you've created through the admin to this repository by sending us a PR. Themes management and customization (you can customize admin title, logo and colors). Responsive, related modal (instead of the old popup window), environment name/marker, language chooser, list filter dropdown. -
3
Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase,... -
4
SHAP
A game theoretic approach to explain the output of ml models
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions. While SHAP can explain the output of any machine learning model, we have developed a high-speed exact algorithm for tree ensemble methods. Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark... -
Paessler - Monitor Your Whole Network in MinutesWaiting weeks for a monitoring rollout isn't an option when infrastructure doesn't stop running. PRTG's auto-discovery scans your network and suggests from over 200 pre-configured sensor types, so you're watching servers, applications and devices within minutes, not after a multi-week deployment. Enterprise-strength monitoring, without the enterprise complexity. Start your free trial today.
-
5
TimesFM
Pretrained time-series foundation model developed by Google Research
TimesFM is a pretrained time-series foundation model from Google Research built for forecasting tasks, designed to generalize across many domains without requiring extensive per-dataset retraining. It provides a decoder-only model approach to forecasting, aiming for strong performance even in zero-shot or low-data settings where traditional models often struggle. The project includes code and an inference API intended to make it practical to run forecasts programmatically, with options to... -
6
QuantumOptics.jl
Library for the numerical simulation of closed as well as open quantum
QuantumOptics.jl is a numerical framework written in the Julia programming language that makes it easy to simulate various kinds of open quantum systems. It is inspired by the Quantum Optics Toolbox for MATLAB and the Python framework QuTiP. QuantumOptics.jl optimizes processor usage and memory consumption by relying on different ways to store and work with operators. The framework comes with a plethora of pre-defined systems and interactions making it very easy to focus on the physics, not... -
7
qaqarot
Quantum Computer Library for Everyone
The Blueqat project has been renamed the Qaqarot Project because of the branding strategy of blueqat inc. -
8
AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. 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,... -
9
-
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
-
10
Jianying Headless
Native Jianying drafts, isolated editing/export
Jianying Headless is a local automation toolkit for creating and editing Jianying Pro video projects on macOS. Structured editing plans can generate editable drafts with multiple video, audio, text, and overlay tracks. Existing projects can be modified inside isolated copies so the original draft is not overwritten. The system supports local media, fonts, keyframes, selected masks, transitions, and native MP4 export through an installed Jianying engine. A Python command-line interface and... -
11
ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
ThinkStats2 is the code and text companion for the second edition of Think Stats, an introduction to statistics and data science for Python programmers. It teaches probability and statistical reasoning through short programs, experiments, and analysis of real datasets. The material emphasizes exploratory methods that help readers ask and answer practical questions with data. Case studies draw from public sources, including health-related datasets, to connect abstract concepts with realistic... -
12
Pixal3D
Pixel-Aligned 3D Generation from Images
Pixal3D is a TencentARC research project for generating high-fidelity 3D assets from a single input image. It addresses a key weakness in image-to-3D generation: many models produce plausible 3D shapes but fail to preserve pixel-level faithfulness to the original image. Pixal3D improves this by explicitly lifting image features into 3D through back-projection, creating clearer correspondences between the input pixels and the generated asset. The system is designed to produce detailed... -
13
VidGear
A High-performance cross-platform Video Processing Python framework
VidGear is a high-performance Python framework that provides a unified and extensible solution for building real-time video processing applications. It acts as an abstraction layer over powerful multimedia libraries such as OpenCV, FFmpeg, and ZeroMQ, simplifying complex workflows into concise and efficient APIs. The framework is built around modular components called “gears,” each responsible for tasks such as video capture, streaming, encoding, and network transmission. It supports... -
14
Pixelle-Video
AI Fully Automated Short Video Engine
Pixelle-Video is an AI-driven system designed for generating and processing video content using modern generative techniques. It focuses on enabling automated video creation workflows where visual content can be synthesized, edited, or enhanced through AI models. The project integrates different components of video processing, such as frame generation, transformation, and sequencing, into a unified pipeline. It is built to support experimentation with generative video models, making it... -
15
Cal.diy
Scheduling infrastructure for absolutely everyone
The Cal.diy project is a fully open-source, self-hosted scheduling platform that provides an alternative to proprietary booking tools while giving users complete control over their infrastructure. It is a community-driven fork of Cal.com that removes all enterprise and commercial features, ensuring that the entire codebase remains MIT-licensed and accessible. The platform enables users to manage bookings, availability, and integrations without relying on external services or subscription... -
16
Nothing Ever Happens
Focused async Python bot for Polymarket
Nothing Ever Happens is an experimental open-source trading bot designed for the Polymarket platform that implements a deliberately simple and unconventional strategy: automatically buying “No” positions across non-sports binary prediction markets. The project is built in Python using asynchronous architecture, allowing it to monitor markets, evaluate opportunities, and execute trades continuously with minimal latency. Its core concept is based on statistical observations that a majority of... -
17
Clawith
OpenClaw for Teams
Clawith is an AI-driven agent system focused on enabling intelligent task execution, coordination, and interaction across complex environments. It is designed to function as a control layer where agents can perform actions, manage workflows, and respond dynamically to changing conditions. The system likely emphasizes integration with external tools and services, allowing agents to extend their capabilities beyond internal reasoning. Its architecture suggests support for multi-agent... -
18
CommunityScrapers
This is a public repository containing scrapers
Stash Community Scrapers is a large open-source collection of metadata extraction tools designed to work with the Stash media management platform, enabling automated scraping of content information from various online sources. The repository contains hundreds of scraper definitions written primarily in YAML and Python, each tailored to extract structured metadata such as titles, performers, tags, and media details from specific websites. These scrapers integrate directly into Stash, allowing... -
19
ToolUniverse
Democratizing AI scientists with ToolUniverse
ToolUniverse is a comprehensive open-source ecosystem designed to transform any large language model into an autonomous “AI scientist” capable of performing real scientific research tasks through structured tool interaction. It standardizes how AI systems discover, select, and execute tools by introducing a unified AI-Tool Interaction Protocol that allows models to seamlessly connect with hundreds of scientific resources, including machine learning models, datasets, APIs, and analytical... -
20
Watermark-Removal
Machine learning image inpainting task that removes watermarks
Watermark-Removal repository is a machine learning project focused on removing visible watermarks from digital images using deep learning and image inpainting techniques. The system analyzes an image containing a watermark and attempts to reconstruct the underlying visual content so that the watermark is removed while preserving the original appearance of the image. The project uses neural network models inspired by research in contextual attention and gated convolution, which are methods... -
21
machine_learning_examples
A collection of machine learning examples and tutorials
machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. The repository covers a wide range of topics including... -
22
tldw Server
Your Personal Research Multi-Tool
tldw-server (mirror) is a mirrored distribution of an open-source backend service designed to store, process, and serve summarized information extracted from long pieces of content. The name “tldw” reflects the phrase “too long; didn’t watch,” which refers to tools that condense lengthy videos, articles, or documents into concise summaries. The server component typically acts as the core infrastructure that manages summaries, metadata, and retrieval operations for client applications or user... -
23
Chitu
High-performance inference framework for large language models
Chitu is a high-performance inference engine designed to deploy and run large language models efficiently in production environments. The framework focuses on improving efficiency, flexibility, and scalability for organizations that need to run LLM inference workloads across different hardware platforms. It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations.... -
24
FlagEmbedding
Retrieval and Retrieval-augmented LLMs
FlagEmbedding is an open-source toolkit for building and deploying high-performance text embedding models used in information retrieval and retrieval-augmented generation systems. The project is part of the BAAI FlagOpen ecosystem and focuses on creating embedding models that transform text into dense vector representations suitable for semantic search and large language model pipelines. FlagEmbedding includes a family of models known as BGE (BAAI General Embedding), which are designed to... -
25
alive-progress
A new kind of Progress Bar, with real-time throughput, ETA
alive-progress is an advanced Python progress bar library that introduces a highly animated and adaptive approach to tracking long-running tasks. Unlike traditional static progress indicators, it dynamically adjusts spinner speed and visual feedback based on actual throughput, giving users a more intuitive sense of activity. The library is designed with performance efficiency in mind, using multithreaded updates that minimize CPU overhead and terminal noise. It includes sophisticated ETA...
