Showing 2819 open source projects for "q-learning"

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  • 1
    DeepLabCut

    DeepLabCut

    Implementation of DeepLabCut

    DeepLabCut™ is an efficient method for 2D and 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results (i.e. you can match human labeling accuracy) with minimal training data (typically 50-200 frames). We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. The package is open source, fast, robust, and can be used to compute 3D pose estimates...
    Downloads: 2 This Week
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  • 2

    LightGBM

    Gradient boosting framework based on decision tree algorithms

    LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle large...
    Downloads: 2 This Week
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  • 3
    deepdoctection

    deepdoctection

    A Repo For Document AI

    DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for fine-tuning...
    Downloads: 2 This Week
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  • 4
    CV-CUDA

    CV-CUDA

    CV-CUDA™ is an open-source, GPU accelerated library

    CV-CUDA is an open-source project that enables building efficient cloud-scale Artificial Intelligence (AI) imaging and computer vision (CV) applications. It uses graphics processing unit (GPU) acceleration to help developers build highly efficient pre- and post-processing pipelines. CV-CUDA originated as a collaborative effort between NVIDIA and ByteDance.
    Downloads: 2 This Week
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  • 5
    BackgroundMattingV2

    BackgroundMattingV2

    Real-Time High-Resolution Background Matting

    Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires capturing an additional background image and produces state-of-the-art matting results at 4K 30fps and HD 60fps on an Nvidia RTX 2080 TI GPU.
    Downloads: 2 This Week
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  • 6
    MedicalGPT

    MedicalGPT

    MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training

    MedicalGPT training medical GPT model with ChatGPT training pipeline, implementation of Pretraining, Supervised Finetuning, Reward Modeling and Reinforcement Learning. MedicalGPT trains large medical models, including secondary pre-training, supervised fine-tuning, reward modeling, and reinforcement learning training.
    Downloads: 2 This Week
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  • 7
    Diffgram

    Diffgram

    Training data (data labeling, annotation, workflow) for all data types

    ... the activities of annotation, which produces structured data; ready to be consumed by a machine learning model. Annotation is required because raw media is considered to be unstructured and not usable without it. That’s why training data is required for many modern machine learning use cases including computer vision, natural language processing and speech recognition.
    Downloads: 2 This Week
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  • 8
    Chronos Forecasting

    Chronos Forecasting

    Pretrained (Language) Models for Probabilistic Time Series Forecasting

    Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as...
    Downloads: 2 This Week
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  • 9
    Lance

    Lance

    Modern columnar data format for ML and LLMs implemented in Rust

    Lance is a columnar data format that is easy and fast to version, query and train on. It’s designed to be used with images, videos, 3D point clouds, audio and of course tabular data. It supports any POSIX file systems, and cloud storage like AWS S3 and Google Cloud Storage.
    Downloads: 2 This Week
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  • 10
    stdlib

    stdlib

    Standard library for JavaScript and Node.js

    A standard library for javascript and node.js. High performance, rigorous, and robust mathematical and statistical functions. Build advanced statistical models and machine learning libraries. Plotting and graphics functionality for data visualization and exploratory data analysis. Analyze and understand your data. Comprehensively tested utilities for application and library development. Functions to assert, group, filter, map, pluck, and transform your data both in browsers and on the server...
    Downloads: 2 This Week
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  • 11
    TF2DeepFloorplan

    TF2DeepFloorplan

    TF2 Deep FloorPlan Recognition using a Multi-task Network

    TF2 Deep FloorPlan Recognition using a Multi-task Network with Room-boundary-Guided Attention. Enable tensorboard, quantization, flask, tflite, docker, github actions and google colab. This repo contains a basic procedure to train and deploy the DNN model suggested by the paper 'Deep Floor Plan Recognition using a Multi-task Network with Room-boundary-Guided Attention'. It rewrites the original codes from zlzeng/DeepFloorplan into newer versions of Tensorflow and Python.
    Downloads: 2 This Week
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  • 12
    PostgresML

    PostgresML

    The GPU-powered AI application database

    PostgresML is a complete platform in a PostgreSQL extension. Build simpler, faster, and more scalable models right inside your database. Explore the SDK and test open source models in our hosted database. Combine and automate the entire workflow from embedding generation to indexing and querying for the simplest (and fastest) knowledge-based chatbot implementation. Leverage multiple types of natural language processing and machine learning models such as vector search and personalization...
    Downloads: 2 This Week
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  • 13
    The SpeechBrain Toolkit

    The SpeechBrain Toolkit

    A PyTorch-based Speech Toolkit

    ... in a wide variety of realistic applications. SpeechBrain provides different models for speaker recognition, including X-vector, ECAPA-TDNN, PLDA, and contrastive learning. Spectral masking, spectral mapping, and time-domain enhancement are different methods already available within SpeechBrain. Separation methods such as Conv-TasNet, DualPath RNN, and SepFormer are implemented as well. SpeechBrain provides efficient and GPU-friendly speech augmentation pipelines and acoustic features extraction.
    Downloads: 2 This Week
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  • 14
    Learn Go with Tests

    Learn Go with Tests

    Learn Go with test-driven development

    Katas are fun but they are usually limited in their scope for learning a language; you're unlikely to use goroutines to solve a kata. Another problem is when you have varying levels of enthusiasm. Some people just learn way more of the language than others and when demonstrating what they have done end up confusing people with features the others are not familiar with. This ends up making the learning feel quite unstructured and ad hoc. By far the most effective way was by slowly introducing...
    Downloads: 2 This Week
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  • 15
    D2L.ai

    D2L.ai

    Interactive deep learning book with multi-framework code

    Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge. This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code. Offers sufficient technical depth...
    Downloads: 1 This Week
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  • 16
    FEATool Multiphysics

    FEATool Multiphysics

    Physics Simulation Made Easy" (Fully Integrated FEA, FEniCS

    FEATool Multiphysics (short for Finite Element Analysis Toolbox), is a fully integrated simulation platform for modeling all types of coupled physics phenomena, continuum mechanics, and engineering problems. By providing a truly easy to use and integrated all-in-one simulation platform for multi-physics analysis, makes FEATool an ideal simulation and modeling tool for everyone from students learning mathematical modeling, to researchers and engineers wishing to explore new ideas in a no fuss...
    Downloads: 2 This Week
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  • 17
    DIG

    DIG

    A library for graph deep learning research

    The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop...
    Downloads: 1 This Week
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  • 18
    NautilusTrader

    NautilusTrader

    A high-performance algorithmic trading platform

    NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, provides quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes. The platform is 'AI-first', designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python native environment. This helps to address the...
    Downloads: 2 This Week
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  • 19
    marimo

    marimo

    A reactive notebook for Python

    marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots,...
    Downloads: 2 This Week
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  • 20
    Feast

    Feast

    Feature Store for Machine Learning

    Feast (Feature Store) is an open source feature store for machine learning. Feast is the fastest path to manage existing infrastructure to productionize analytic data for model training and online inference. Make features consistently available for training and serving by managing an offline store (to process historical data for scale-out batch scoring or model training), a low-latency online store (to power real-time prediction), and a battle-tested feature server (to serve pre-computed...
    Downloads: 2 This Week
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  • 21
    ACHE Focused Crawler

    ACHE Focused Crawler

    ACHE is a web crawler for domain-specific search

    ACHE is a focused web crawler. It collects web pages that satisfy some specific criteria, e.g., pages that belong to a given domain or that contain a user-specified pattern. ACHE differs from generic crawlers in sense that it uses page classifiers to distinguish between relevant and irrelevant pages in a given domain. A page classifier can be defined as a simple regular expression (e.g., that matches every page that contains a specific word) or a machine-learning-based classification model...
    Downloads: 2 This Week
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  • 22
    Pytorch-toolbelt

    Pytorch-toolbelt

    PyTorch extensions for fast R&D prototyping and Kaggle farming

    A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses:...
    Downloads: 2 This Week
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  • 23
    torchtext

    torchtext

    Data loaders and abstractions for text and NLP

    We recommend Anaconda as a Python package management system. Please refer to pytorch.org for the details of PyTorch installation. LTS versions are distributed through a different channel than the other versioned releases. Alternatively, you might want to use the Moses tokenizer port in SacreMoses (split from NLTK). You have to install SacreMoses. To build torchtext from source, you need git, CMake and C++11 compiler such as g++. When building from source, make sure that you have the same C++...
    Downloads: 2 This Week
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  • 24
    Freqtrade

    Freqtrade

    Free, open source crypto trading bot

    Freqtrade is a free and open-source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or WebUI. It contains backtesting, plotting, and money management tools as well as strategy optimization by machine learning. Always start by running a trading bot in Dry-run and do not engage money before you understand how it works and what profit/loss you should expect. We strongly recommend you have basic coding skills and Python knowledge...
    Downloads: 2 This Week
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  • 25
    JUDI.jl

    JUDI.jl

    Julia Devito inversion

    ... operators can also be used as layers in (convolutional) neural networks to implement physics-augmented deep learning algorithms thanks to its implementation of ChainRules's rrule for the linear operators representing the discre wave equation.
    Downloads: 2 This Week
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