Search Results for "multi-layer perceptron python"
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Showing 237 open source projects for "multi-layer perceptron python"
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RKN Block Checker
Diagnose RKN/TSPU internet blocks layer by layer (DNS, TCP, TLS, HTTP)
RKN Block Checker is a small Python CLI for diagnosing whether the current network connection is affected by Russian RKN or TSPU blocking. It tests blocking behavior layer by layer instead of only reporting that a site is unreachable. The tool can help distinguish DNS poisoning, TCP reset behavior, TLS DPI based on SNI, and ISP stub pages. This makes it useful for developers, system administrators, network researchers, and censorship-measurement workflows. -
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Kivy
Innovative user interfaces made easy
Kivy is an open source, cross-platform UI framework that lets you develop applications that make use of innovative, multi-touch user interfaces. Written in Python with a graphics engine built over OpenGL ES 2, Kivy supports various input devices and protocols, and gives you access to over 20 widgets that are all highly extensible and have built-in multi-touch support. You can run the same codebase on Mac, Windows, Linux, Android and iOS. Kivy is 100% free and open source with a professionally developed and used toolkit, as well as a stable framework and well-documented API, so you can be confident in using it in a commercial product. -
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spyder
The scientific Python development environment
Spyder is a free and open source scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package. -
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PyInstaller
Freeze (package) Python programs into stand-alone executables
PyInstaller freezes (packages) Python applications into stand-alone executables, under Windows, GNU/Linux, Mac OS X, FreeBSD, Solaris and AIX. PyInstaller’s main advantages over similar tools are that PyInstaller works with Python 3.5 to 3.9, it builds smaller executables thanks to transparent compression, it is fully multi-platform, and use the OS support to load the dynamic libraries, thus ensuring full compatibility. -
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TurboGears
Python web framework with full-stack layer
TurboGears is a hybrid web framework able to act both as a Full Stack framework or as a Microframework. TurboGears helps you get going fast and gets out of your way when you want it! TurboGears can be used both as a full stack framework or as a microframework in single-file mode. TurboGears 2 is built on top of the experience of several next-generation web frameworks including TurboGears 1 (of course), Django, and Rails. All of these frameworks had limitations that frustrated us, and TG2 was... -
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AIMET
AIMET is a library that provides advanced quantization and compression
Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware... -
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PAL MCP
The power of Claude Code / GeminiCLI / CodexCLI
PAL MCP is an open-source Model Context Protocol (MCP) server designed to act as a powerful middleware layer that connects AI clients and tools—like Claude Code, Codex CLI, Cursor, and IDE plugins—to a broad range of underlying AI models, enabling collaborative multi-model workflows rather than relying on a single model. It lets developers orchestrate interactions across multiple models (including Gemini, OpenAI, Grok, Azure, Ollama, OpenRouter, and custom/self-hosted models), preserving... -
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Flax
Flax is a neural network library for JAX
Flax is a flexible neural-network library for JAX that embraces functional programming while offering ergonomic module abstractions. Its design separates pure computation from state by threading parameter collections and RNGs explicitly, enabling reproducibility, transformation, and easy experimentation with JAX transforms like jit, pmap, and vmap. Modules define parameterized computations, but initialization and application remain side-effect free, which pairs naturally with JAX’s staging... -
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AG-UI
The Agent-User Interaction Protocol
AG-UI is an open, lightweight protocol for connecting AI agents to user-facing applications through a standardized event-based interface. It is designed to make agent behavior visible, interactive, and controllable inside real-time front-end experiences. Instead of treating an AI agent as a black-box chat endpoint, AG-UI defines structured events for messages, tool calls, state changes, lifecycle updates, and user interactions. This makes it easier for developers to build agent-powered apps... -
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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Smallpond
A lightweight data processing framework built on DuckDB and 3FS
smallpond is a lightweight distributed data processing framework built by DeepSeek, designed to scale DuckDB workloads over clusters using their 3FS (Fire-Flyer File System) backend. The idea is to preserve DuckDB’s fast analytics engine but lift it from single-node to multi-node settings, giving you the ability to operate on large datasets (e.g. petabyte scale) without moving to a heavyweight system like Spark. Users write Python-like code (via DataFrame APIs or SQL strings) to express their transformations; behind the scenes, tasks are scheduled (often via Ray) and pushed into DuckDB instances operating on partitioned data. ... -
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PydanticAI
Agent Framework / shim to use Pydantic with LLMs
When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. Built by the team behind Pydantic (the validation layer of the OpenAI SDK, the Anthropic SDK, LangChain, LlamaIndex, AutoGPT, Transformers, CrewAI, Instructor, and many more). -
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PlatformIO Core
Professional collaborative platform for embedded development
PlatformIO is a professional collaborative platform for embedded development. A place where Developers and Teams have true Freedom! No more vendor lock-in! A user-friendly and extensible integrated development environment with a set of professional development instruments, providing modern and powerful features to speed up yet simplify the creation and delivery of embedded products. A lightweight but powerful cross-platform source code editor. Smart code completions are based on variable... -
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OWL
Optimized Workforce Learning for General Multi-Agent Assistance
OWL (Optimized Workforce Learning) is a sophisticated open-source framework built on the CAMEL-AI ecosystem for orchestrating teams of AI agents to collaboratively solve complex, real-world tasks with dynamic planning and automation capabilities. Unlike single-agent systems, it treats task completion as a collaborative workforce where agents take on specialized roles (planning, execution, analysis) and coordinate via a modular multi-agent architecture that supports flexible teamwork across... -
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julep
A new DSL and server for AI agents and multi-step tasks
Julep is a platform for creating AI agents that remember past interactions and can perform complex tasks. It offers long-term memory and manages multi-step processes. Julep enables the creation of multi-step tasks incorporating decision-making, loops, parallel processing, and integration with numerous external tools and APIs. While many AI applications are limited to simple, linear chains of prompts and API calls with minimal branching, Julep is built to handle more complex scenarios. -
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any-llm
Communicate with an LLM provider using a single interface
any-llm is a unified SDK and platform developed by Mozilla AI that allows developers to interact with multiple large language model providers through a single, consistent interface. Instead of rewriting code for each provider, developers can switch between services like OpenAI, Anthropic, Mistral, and Ollama simply by changing configuration parameters. The project is designed to be framework-agnostic, making it easy to integrate into scripts, applications, or production systems without being... -
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nature-skills
Skill that conforms to the academic expression and scientific research
nature-skills is an open-source collection of AI agent skills and structured workflows designed to enhance autonomous reasoning and tool usage in AI assistants. The project organizes reusable “skills” that agents can invoke for different operational contexts, helping AI systems perform specialized tasks more consistently and effectively. It appears to focus on modularity and interoperability, allowing skills to be combined, extended, or integrated into broader agent ecosystems. The... -
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CuPy
A NumPy-compatible array library accelerated by CUDA
CuPy is an open source implementation of NumPy-compatible multi-dimensional array accelerated with NVIDIA CUDA. It consists of cupy.ndarray, a core multi-dimensional array class and many functions on it. CuPy offers GPU accelerated computing with Python, using CUDA-related libraries to fully utilize the GPU architecture. According to benchmarks, it can even speed up some operations by more than 100X. -
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Hera
Hera is an Argo Python SDK
Hera is an Argo Python SDK. Hera aims to make the construction and submission of various Argo Project resources easy and accessible to everyone! Hera abstracts away low-level setup details while still maintaining a consistent vocabulary with Argo. -
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Cython
The most widely used Python to C compiler
Cython is an optimizing static compiler for both the Python programming language and the extended Cython programming language (based on Pyrex). It makes writing C extensions for Python as easy as Python itself. Write Python code that calls back and forth from and to C or C++ code natively at any point. Easily tune readable Python code into plain C performance by adding static type declarations, also in Python syntax. -
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Flet
Flet enables developers to easily build realtime web and mobile apps
...With Flet you just write a monolith stateful app in Python only and get a multi-user, real-time Single-Page Application (SPA). To start developing with Flet, you just need your favorite IDE or text editor. With no SDKs, no thousands of dependencies, no complex tooling, Flet has a built-in web server with assets hosting and desktop clients. -
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TradingAgents
Chinese Financial Trading Framework Based on Multi-Agent LLM
TradingAgents-CN is a Chinese-enhanced, multi-agent LLM framework aimed at building financial analysis and trading-oriented workflows, with an emphasis on collaboration between specialized agents rather than a single monolithic prompt. It organizes market-related tasks into roles and stages so different agents can contribute research, reasoning, aggregation, and decision support in a structured pipeline. The project is oriented toward practical usage, including a stack that can be run in a... -
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. ... -
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Terraform Examples and Modules for GC
End-to-end modular samples and landing zones toolkit for Terraform
Terraform Examples and Modules for GC is a comprehensive infrastructure-as-code toolkit built on Terraform that enables organizations to design, deploy, and manage enterprise-grade Google Cloud environments using modular and reusable components. It provides a collection of end-to-end blueprints and composable modules that allow teams to implement standardized cloud architectures such as landing zones, networking configurations, and security frameworks. The project is designed to accelerate... -
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NetworkX
Network analysis in Python
...Edges can hold arbitrary data (e.g., weights, time-series). Open source 3-clause BSD license. Well tested with over 90% code coverage. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. Find the shortest path between two nodes in an undirected graph. Python’s None object is not allowed to be used as a node. It determines whether optional function arguments have been assigned in many functions. And it can be used as a sentinel object meaning “not a node”. -
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dynaconf
Configuration Management for Python
Inspired by the 12-factor application guide. Settings management (default values, validation, parsing, templating). Protection of sensitive information (passwords/tokens). Multiple file formats toml|yaml|json|ini|py and also customizable loaders. Full support for environment variables to override existing settings (dotenv support included). Optional layered system for multi environments [default, development, testing, production] (also called multi profiles). Built-in support for Hashicorp...