Search Results for "python q learning" - Page 8

Showing 1664 open source projects for "python q learning"

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  • 1
    DocTR

    DocTR

    Library for OCR-related tasks powered by Deep Learning

    DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document...
    Downloads: 6 This Week
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  • 2
    RL Baselines3 Zoo

    RL Baselines3 Zoo

    Training framework for Stable Baselines3 reinforcement learning agents

    rl-baselines3-zoo is a collection of pre-trained models, benchmarks, and hyperparameter tuning tools built on top of Stable Baselines3, a reinforcement learning library. It provides an easy way to test, evaluate, and train RL agents across a wide variety of environments.
    Downloads: 0 This Week
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  • 3
    Orion

    Orion

    A machine learning library for detecting anomalies in signals

    Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations. Abstract away from the users the nitty-gritty about preprocessing,...
    Downloads: 0 This Week
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  • 4
    AiLearning-Theory-Applying

    AiLearning-Theory-Applying

    Quickly get started with AI theory and practical applications

    AiLearning-Theory-Applying is a comprehensive educational repository designed to help learners quickly understand artificial intelligence theory and apply it in practical machine learning and deep learning projects. The repository provides extensive tutorials covering mathematical foundations, machine learning algorithms, deep learning concepts, and modern large language model architectures. It includes well-commented notebooks, datasets, and implementation examples that allow learners to...
    Downloads: 0 This Week
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    AI Engineer Headquarters

    AI Engineer Headquarters

    A collection of scientific methods, processes, algorithms

    AI-Engineer-Headquarters is a comprehensive educational repository designed to help developers become advanced AI engineers through a structured learning path and practical system-building exercises. The project serves as a curated collection of resources, methodologies, and tools covering topics across the entire artificial intelligence development lifecycle. Rather than focusing only on theoretical knowledge, the repository emphasizes applied learning and encourages engineers to build real...
    Downloads: 0 This Week
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  • 6
    Causal ML

    Causal ML

    Uplift modeling and causal inference with machine learning algorithms

    Causal ML is a Python package that provides a suite of uplift modeling and causal inference methods using machine learning algorithms based on recent research [1]. It provides a standard interface that allows users to estimate the Conditional Average Treatment Effect (CATE) or Individual Treatment Effect (ITE) from experimental or observational data.
    Downloads: 0 This Week
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  • 7
    Triton

    Triton

    Development repository for the Triton language and compiler

    Triton is a programming language and compiler framework specifically designed for writing highly efficient custom deep learning operations, particularly for GPUs. It aims to bridge the gap between low-level GPU programming, such as CUDA, and higher-level abstractions by providing a more productive and flexible environment for developers. Triton enables users to write optimized kernels for machine learning workloads while maintaining readability and control over performance-critical aspects...
    Downloads: 4 This Week
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  • 8
    TNT

    TNT

    A lightweight library for PyTorch training tools and utilities

    TNT is a lightweight training framework developed by Meta that simplifies the process of building and managing machine learning training loops using PyTorch. The project focuses on providing a flexible yet structured environment for implementing training pipelines without the complexity of large deep learning frameworks. It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps...
    Downloads: 0 This Week
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  • 9
    SpikingJelly

    SpikingJelly

    SpikingJelly is an open-source deep learning framework

    SpikingJelly is an open-source deep learning framework for spiking neural networks that is primarily built on top of PyTorch and aimed at neuromorphic computing research. The project provides the components needed to build, train, and evaluate neural models that communicate through discrete spikes rather than the continuous activations used in conventional artificial neural networks. This makes it especially relevant for researchers interested in biologically inspired computing, event-driven...
    Downloads: 3 This Week
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  • 10
    Sapiens

    Sapiens

    High-resolution models for human tasks

    Sapiens is a research framework from Meta AI focused on embodied intelligence and human-like multimodal learning, aiming to train agents that can perceive, reason, and act in complex environments. It integrates sensory inputs such as vision, audio, and proprioception into a unified learning architecture that allows agents to understand and adapt to their surroundings dynamically. The project emphasizes long-horizon reasoning and cross-modal grounding—connecting language, perception, and...
    Downloads: 3 This Week
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  • 11
    Transformer Engine

    Transformer Engine

    A library for accelerating Transformer models on NVIDIA GPUs

    Transformer Engine (TE) is a library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper GPUs, to provide better performance with lower memory utilization in both training and inference. TE provides a collection of highly optimized building blocks for popular Transformer architectures and an automatic mixed precision-like API that can be used seamlessly with your framework-specific code. TE also includes a framework-agnostic C++...
    Downloads: 5 This Week
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  • 12
    RAGFlow

    RAGFlow

    RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine

    RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
    Downloads: 22 This Week
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  • 13
    Claude How-To

    Claude How-To

    A visual, example-driven guide to Claude Code

    Claude How-To is a visual, example-driven guide for learning Claude Code. It covers basic concepts, memory, slash commands, hooks, skills, subagents, MCP configuration, plugins, and advanced agent workflows. The project is designed as a practical learning path rather than a simple list of notes. It includes copy-paste templates that users can apply directly to their own projects. The guide also uses diagrams and structured examples to explain not only how features work, but why they matter...
    Downloads: 6 This Week
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  • 14
    ComfyUI-3D-Pack

    ComfyUI-3D-Pack

    An extensive node suite that enables ComfyUI to process 3D inputs

    ComfyUI-3D-Pack is an extension package for the ComfyUI visual AI workflow environment that enables users to generate and manipulate 3D assets using advanced machine learning techniques. ComfyUI itself is a node-based interface for designing and executing generative AI pipelines, and this extension expands its capabilities by introducing nodes specifically designed for working with three-dimensional data. The package allows the platform to process inputs such as meshes and UV textures and...
    Downloads: 11 This Week
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  • 15
    CUDA Containers for Edge AI & Robotics

    CUDA Containers for Edge AI & Robotics

    Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

    CUDA Containers for Edge AI & Robotics is an open-source project that provides a modular container build system designed for running machine learning and AI workloads on NVIDIA Jetson devices. The repository contains container configurations that package the latest AI frameworks and dependencies optimized for Jetson hardware. These containers simplify the deployment of complex machine learning environments by bundling libraries such as CUDA, TensorRT, and deep learning frameworks into...
    Downloads: 0 This Week
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  • 16
    Key-book

    Key-book

    Proofs, cases, concept supplements, and reference explanations

    The book "Introduction to Machine Learning Theory" (hereinafter referred to as "Introduction") written by Zhou Zhihua, Wang Wei, Gao Wei, and other teachers fills the regret of the lack of introductory works on machine learning theory in China. This book attempts to provide an introductory guide for readers interested in learning machine learning theory and researching machine learning theory in an easy-to-understand language. "Guide" mainly covers seven parts, corresponding to seven...
    Downloads: 0 This Week
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  • 17
    Determined

    Determined

    Determined, deep learning training platform

    The fastest and easiest way to build deep learning models. Distributed training without changing your model code. Determined takes care of provisioning machines, networking, data loading, and fault tolerance. Build more accurate models faster with scalable hyperparameter search, seamlessly orchestrated by Determined. Use state-of-the-art algorithms and explore results with our hyperparameter search visualizations. Interpret your experiment results using the Determined UI and TensorBoard, and...
    Downloads: 0 This Week
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  • 18
    Nixtla TimeGPT

    Nixtla TimeGPT

    TimeGPT-1: production ready pre-trained Time Series Foundation Model

    TimeGPT is a production ready, generative pretrained transformer for time series. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code. Whether you're a bank forecasting market trends or a startup predicting product demand, TimeGPT democratizes access to cutting-edge predictive insights, eliminating the need for a dedicated team of machine learning engineers. A generative model for time series. TimeGPT is capable of...
    Downloads: 1 This Week
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  • 19
    FlashAttention

    FlashAttention

    Fast and memory-efficient exact attention

    FlashAttention is a high-performance deep learning optimization library that reimplements the attention mechanism used in transformer models to be significantly faster and more memory-efficient than standard implementations. It achieves this by using IO-aware algorithms that minimize memory reads and writes, reducing the quadratic memory overhead typically associated with attention operations. The project provides implementations of FlashAttention, FlashAttention-2, and newer iterations...
    Downloads: 18 This Week
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  • 20
    omegaml

    omegaml

    MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle

    omega|ml is the innovative Python-native MLOps platform that provides a scalable development and runtime environment for your Data Products. Works from laptop to cloud.
    Downloads: 0 This Week
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  • 21
    VibeTensor

    VibeTensor

    Our first fully AI generated deep learning system

    ...What makes VibeTensor remarkable is that every major component, from core libraries and dispatch systems to CUDA runtime support, caching allocators, and language bindings, was created and validated by coding agents using automated builds and tests rather than manual line-by-line human coding. The system includes both a Python frontend via a torch-like API and an experimental Node.js/TypeScript interface.
    Downloads: 0 This Week
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  • 22
    Open Model Zoo

    Open Model Zoo

    Pre-trained Deep Learning models and demos

    ...In addition to model files, Open Model Zoo provides demo applications that show realistic usage patterns and help developers quickly prototype and understand inference pipelines in C++, Python, or via the OpenCV Graph API. Tools in the repository also help automate model downloads and other tasks, making it easier to incorporate these models into production systems or custom solutions.
    Downloads: 0 This Week
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  • 23
    PaLM + RLHF - Pytorch

    PaLM + RLHF - Pytorch

    Implementation of RLHF (Reinforcement Learning with Human Feedback)

    PaLM-rlhf-pytorch is a PyTorch implementation of Pathways Language Model (PaLM) with Reinforcement Learning from Human Feedback (RLHF). It is designed for fine-tuning large-scale language models with human preference alignment, similar to OpenAI’s approach for training models like ChatGPT.
    Downloads: 0 This Week
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  • 24
    DeepCTR

    DeepCTR

    Package of deep-learning based CTR models

    DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based...
    Downloads: 1 This Week
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  • 25
    TorchCode

    TorchCode

    Practice implementing softmax, attention, GPT-2 and more

    TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms,...
    Downloads: 0 This Week
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