Search Results for "network monitoring tools"
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Showing 8 open source projects for "network monitoring tools"
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DevOps Basics
Practical and document place for DevOps toolchain
You are new to DevOps or want to learn some DevOps tools, or you are already a DevOps engineer, and you are looking for DevOps documents and a place to practice DevOps tools? This repository will assist you in enhancing your DevOps skills and serve as a bookmark for documents related to DevOps. -
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RLax
Library of JAX-based building blocks for reinforcement learning agents
...It supports both on-policy and off-policy learning, as well as value-based, policy-based, and model-based approaches. RLax is fully JIT-compilable with JAX, enabling high-performance execution across CPU, GPU, and TPU backends. The library implements tools for Bellman equations, return distributions, general value functions, and policy optimization in both continuous and discrete action spaces. It integrates seamlessly with DeepMind’s Haiku (for neural network definition) and Optax (for optimization), making it a key component in modular RL pipelines. -
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Generative AI Examples
Generative AI Examples is a collection of GenAI examples
Efficiently integrate secure, performant, and cost-effective Generative AI workflows into business value. Detailed framework of composable building blocks for state-of-the-art generative AI systems including LLMs, data stores, and prompt engines. Architectural blueprints of retrieval-augmented generative AI component stack structure and end-to-end workflows. A four-step assessment for grading generative AI systems around performance, features, trustworthiness and enterprise-grade readiness. -
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Terminals Are Sexy
A curated list of Terminal frameworks, plugins & resources
This repository is a curated, community-driven collection of tools, tips, themes, and resources that make working in the terminal more productive and enjoyable. It pulls together high-quality links to terminal emulators, shells, prompts, plugins, fonts, color schemes, and command-line utilities, alongside learning materials for sharpening everyday CLI skills. The list favors practical, well-maintained projects and is organized so you can quickly discover alternatives for common tasks (navigation, search, networking, monitoring, text processing, and more). ... -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple... -
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PrettyTensor
Pretty Tensor: Fluent Networks in TensorFlow
Pretty Tensor is a high-level API built on top of TensorFlow that simplifies the process of creating and managing deep learning models. It wraps TensorFlow tensors in a chainable object syntax, allowing developers to build multi-layer neural networks with concise and readable code. Pretty Tensor preserves full compatibility with TensorFlow’s core functionality while providing syntactic sugar for defining complex architectures such as convolutional and recurrent networks. The library’s design... -
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Bocker
Docker implemented in around 100 lines of bash
Bocker is a minimal, educational reimplementation of core container (Docker-like) functionality, done in about a hundred lines of Bash script. Its purpose is not to replace Docker’s full feature set, but to illustrate container primitives—namespaces, cgroups, layering, filesystem manipulation, network namespaces, etc.—in a transparent, minimal form. With bocker you can perform basic operations such as pulling an image, running a container, exec into a container, listing containers, and... -
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Universal PHP Framework. toKernel is a fully Object-Oriented extensible framework. By design, the framework's kernel is monolithic which brings a lot of advantages. It is NOT a loader for a mere collection of classes.
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