Search Results for "python q learning" - Page 28
Sort By:
Showing 1618 open source projects for "python q learning"
View related business solutions-
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.
-
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
1
PyTorch Lightning
The lightweight PyTorch wrapper for high-performance AI research
Scale your models, not your boilerplate with PyTorch Lightning! PyTorch Lightning is the ultimate PyTorch research framework that allows you to focus on the research while it takes care of everything else. It's designed to decouple the science from the engineering in your PyTorch code, simplifying complex network coding and giving you maximum flexibility. PyTorch Lightning can be used for just about any type of research, and was built for the fast inference needed in AI research and... -
2
GPTImage2Skill
GPT Image 2 prompt gallery, image prompt library, agentic skill
GPTImage2Skill is a curated prompt gallery, agent skill, and command-line workflow for working with GPT Image 2 generation and editing. It provides reusable image prompts across creative, technical, academic, interface, design, photography, typography, gaming, anime, map, tattoo, and reference-editing use cases. The project is designed to help agents and users produce stronger visual outputs without starting from a blank prompt every time. Its gallery is organized into category files so an... -
3
JAX Toolbox
Public CI, Docker images for popular JAX libraries
JAX Toolbox is a development toolkit designed to streamline and optimize the use of JAX for machine learning and high-performance computing on NVIDIA GPUs. It provides prebuilt Docker images, continuous integration pipelines, and optimized example implementations that help developers quickly set up and run JAX workloads without complex configuration. The project supports popular JAX-based frameworks and models, including architectures used for large-scale pretraining such as GPT and LLaMA... -
4
Google Kubernetes Engine (GKE) Samples
Sample applications for Google Kubernetes Engine (GKE)
Google Kubernetes Engine (GKE) Samples repository is a comprehensive collection of sample applications and reference implementations designed to demonstrate how to build, deploy, and manage workloads on Google Kubernetes Engine (GKE). It serves as a practical companion to official GKE tutorials, providing real, runnable code that illustrates how containerized applications are packaged, deployed, and scaled within Kubernetes clusters. The repository is organized into multiple categories such... -
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.
-
5
Google Research
This repository contains code released by Google Research
Google Research is a massive monorepo that hosts a wide range of research code released by Google Research teams across machine learning, artificial intelligence, robotics, natural language processing, and other advanced domains. Rather than being a single framework, the repository serves as a centralized collection of experimental projects, reference implementations, and reproducible research artifacts. It is intended primarily for researchers and advanced practitioners who want to explore... -
6
aws-devops-zero-to-hero
AWS zero to hero repo for devops engineers to learn AWS in 30 Days
aws-devops-zero-to-hero is a 30-day AWS learning roadmap aimed squarely at DevOps engineers who want both conceptual understanding and hands-on projects. The README is structured as a day-by-day syllabus, starting with “Day 1: Introduction to AWS” and moving through IAM, EC2, VPC networking, security, DNS (Route 53), storage (S3), and many other core services. Each day mixes explanation with at least one concrete project or lab, such as deploying applications on EC2, designing secure VPCs,... -
7
Hello SQL
Spanish-language course repository that teaches fundamentals of SQL
hello-sql is a beginner-friendly, Spanish-language course repository that teaches the fundamentals of SQL and relational databases through practical examples. It focuses mainly on MySQL for lessons due to its ubiquity in education and professional environments, while also introducing PostgreSQL to broaden learners’ exposure to modern database tooling. The materials emphasize real-world query writing, schema design basics, and the mental model behind SELECT, JOIN, GROUP BY, and subqueries.... -
8
PaddleSpeech
Easy-to-use Speech Toolkit including Self-Supervised Learning model
PaddleSpeech is an open-source toolkit on PaddlePaddle platform for a variety of critical tasks in speech and audio, with state-of-art and influential models. Via the easy-to-use, efficient, flexible and scalable implementation, our vision is to empower both industrial application and academic research, including training, inference & testing modules, and deployment process. Low barriers to install, CLI, Server, and Streaming Server is available to quick-start your journey. We provide... -
9
SDGym
Benchmarking synthetic data generation methods
The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the... -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
10
HelloGitHub
Share interesting, entry-level open source projects on GitHub
HelloGitHub shares interesting, entry-level open source projects on GitHub. It is updated and released in the form of a monthly magazine on the 28th of every month. The content includes interesting, entry-level open-source projects, open-source books, practical projects, enterprise-level projects, etc., so that you can feel the charm of open source in a short time and fall in love with open source! At first, I just wanted to collect interesting, high-quality, and easy-to-use projects that I... -
11
Colab-MCP
An MCP server for interacting with Google Colab
Colab-MCP is an open-source Model Context Protocol server developed by Google that enables AI agents to directly interact with and control Google Colab environments programmatically, transforming Colab into a fully automated, agent-accessible workspace. Instead of relying on manual notebook usage, the system allows MCP-compatible agents to execute code, manage files, install dependencies, and orchestrate entire development workflows within Colab’s cloud infrastructure. This approach bridges... -
12
Pixeltable
Data Infrastructure providing an approach to multimodal AI workloads
Pixeltable is an open-source Python data infrastructure framework designed to support the development of multimodal AI applications. The system provides a declarative interface for managing the entire lifecycle of AI data pipelines, including storage, transformation, indexing, retrieval, and orchestration of datasets. Unlike traditional architectures that require multiple tools such as databases, vector stores, and workflow orchestrators, Pixeltable unifies these functions within a... -
13
Amazon Braket PennyLane Plugin
A plugin for allowing Xanadu PennyLane to use Amazon Braket devices
The Amazon Braket PennyLane plugin offers two Amazon Braket quantum devices to work with PennyLane. The Amazon Braket Python SDK is an open-source library that provides a framework to interact with quantum computing hardware devices and simulators through Amazon Braket. PennyLane is a machine learning library for optimization and automatic differentiation of hybrid quantum-classical computations. Once the Pennylane-Braket plugin is installed, the provided Braket devices can be accessed straight away in PennyLane, without the need to import any additional packages. ... -
14
LinuxPlay
An open-source, ultra-low-latency remote desktop for Linux hosts
LinuxPlay is a multimedia playback project designed to provide a lightweight media player for Linux environments with support for common audio and video formats. It focuses on implementing playback functionality using FFmpeg and native Linux APIs to ensure efficient decoding and rendering. The project demonstrates how to build a media player from scratch, including handling audio-video synchronization and playback controls. It supports local file playback and may include streaming... -
15
autoresearch-win-rtx
AI agents running research on single-GPU nanochat training
autoresearch-win-rtx is a Windows-based implementation of the autoresearch framework designed to run autonomous AI research loops on consumer NVIDIA RTX GPUs. It adapts the original autoresearch concept to a Windows environment, enabling users to perform iterative machine learning optimization without requiring specialized Linux or data center setups. The system revolves around a small set of core files, including a training script that is continuously modified by an AI agent, along with... -
16
NVIDIA Model Optimizer
A unified library of SOTA model optimization techniques
Model Optimizer is a unified library that provides state-of-the-art techniques for compressing and optimizing deep learning models to improve inference efficiency and deployment performance. It brings together multiple optimization strategies such as quantization, pruning, distillation, and speculative decoding into a single cohesive framework. The library is designed to reduce model size and computational requirements while maintaining accuracy, making it particularly valuable for deploying... -
17
SimpleLLM
950 line, minimal, extensible LLM inference engine built from scratch
SimpleLLM is a minimal, extensible large language model inference engine implemented in roughly 950 lines of code, built from scratch to serve both as a learning tool and a research platform for novel inference techniques. It provides the core components of an LLM runtime—such as tokenization, batching, and asynchronous execution—without the abstraction overhead of more complex engines, making it easier for developers and researchers to understand and modify. Designed to run efficiently on... -
18
AWorld
Build, evaluate and train General Multi-Agent Assistance with ease
AWorld (Agent World) is an agent runtime/framework. It supports building, evaluating, and training self-improving intelligent agents and multi-agent systems (MAS). It is designed to provide infrastructure for agent orchestration, iterative learning, and environment interaction at scale. Scalable training across environments and distributed setups. Support for multi-agent collaboration/orchestration (MAS). The system is intended to help agents evolve via experience. It provides features to... -
19
Otter-Grader
A Python and R autograding solution
...It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an Otter-managed grading virtual machine, and a client package that allows students to run public checks on their own machines. Otter is designed to grade Python scripts and Jupyter Notebooks, and is compatible with a few different LMSs, including Canvas and Gradescope. -
20
PaSa
An advanced paper search agent powered by large language models
PaSa is an open-source “paper search agent” built around large language models (LLMs), designed to automate the process of academic literature retrieval with human-like decision making. Instead of simply translating a query into keywords and returning a flat list of matching papers, PaSa uses a dual-agent architecture (Crawler + Selector) that can iteratively search, read, analyze, and filter academic publications — simulating how a researcher might dig through citation networks, expand... -
21
Step-Audio-EditX
LLM-based Reinforcement Learning audio edit model
Step-Audio-EditX is an open-source, 3 billion-parameter audio model from StepFun AI designed to make expressive and precise editing of speech and audio as easy as text editing. Rather than treating audio editing as low-level waveform manipulation, this model converts speech into a sequence of discrete “audio tokens” (via a dual-codebook tokenizer) — combining a linguistic token stream and a semantic (prosody/emotion/style) token stream — thereby abstracting audio editing into high-level... -
22
MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
MiniMax-M1 is presented as the world’s first open-weight, large-scale hybrid-attention reasoning model, designed to push the frontier of long-context, tool-using, and deeply “thinking” language models. It is built on the MiniMax-Text-01 foundation and keeps the same massive parameter budget, but reworks the attention and training setup for better reasoning and test-time compute scaling. Architecturally, it combines Mixture-of-Experts layers with lightning attention, enabling the model to... -
23
Grafana
Leading open-source visualization and observability platform
Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. Users can build interactive dashboards with rich... -
24
OpenSRE
Build your own AI SRE agents. The open source toolkit for the AI era
OpenSRE is an open-source framework designed to build AI-powered Site Reliability Engineering agents that automate incident investigation and root cause analysis across modern cloud environments. It connects to observability tools, infrastructure systems, and communication platforms to gather logs, metrics, and traces in real time. When an alert is triggered, the system autonomously analyzes correlated signals, identifies anomalies, and generates structured investigation reports with... -
25
Hugging Face - Speech To Speech
Open speech-to-speech models and pipelines by Hugging Face toolkit AI
This project from Hugging Face focuses on enabling direct speech-to-speech processing using modern machine learning models. It provides tools and reference implementations that allow audio input to be transformed into audio output without requiring an intermediate text representation. Hugging Face - Speech To Speech builds on recent advances in speech modeling, combining components such as speech recognition, translation, and synthesis into unified pipelines. It is designed to help...
