Search Results for "python q learning" - Page 50

Showing 1633 open source projects for "python q learning"

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  • 1
    PORORO

    PORORO

    Platform of neural models for natural language processing

    pororo performs Natural Language Processing and Speech-related tasks. It is easy to solve various subtasks in the natural language and speech processing field by simply passing the task name. Recognized speech sentences using the trained model. Currently English, Korean and Chinese support. Get vector or find similar words and entities from pretrained model using Wikipedia.
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  • 2
    PyTorch SimCLR

    PyTorch SimCLR

    PyTorch implementation of SimCLR: A Simple Framework

    For quite some time now, we know about the benefits of transfer learning in Computer Vision (CV) applications. Nowadays, pre-trained Deep Convolution Neural Networks (DCNNs) are the first go-to pre-solutions to learn a new task. These large models are trained on huge supervised corpora, like the ImageNet. And most important, their features are known to adapt well to new problems. This is particularly interesting when annotated training data is scarce. In situations like this, we take the...
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  • 3
    PaddlePaddle models

    PaddlePaddle models

    Pre-trained and Reproduced Deep Learning Models

    Pre-trained and Reproduced Deep Learning Models ("Flying Paddle" official model library, including a variety of academic frontier and industrial scene verification of deep learning models) Flying Paddle's industrial-level model library includes a large number of mainstream models that have been polished by industrial practice for a long time and models that have won championships in international competitions; it provides many scenarios for semantic understanding, image classification,...
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  • 4
    Keras TCN

    Keras TCN

    Keras Temporal Convolutional Network

    TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the...
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  • 5
    BudgetML

    BudgetML

    Deploy a ML inference service on a budget in 10 lines of code

    Deploy a ML inference service on a budget in less than 10 lines of code. BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST,...
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  • 6
    Bayesian machine learning notebooks

    Bayesian machine learning notebooks

    Notebooks about Bayesian methods for machine learning

    Notebooks about Bayesian methods for machine learning.
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  • 7
    TensorLayer

    TensorLayer

    Deep learning and reinforcement learning library for scientists

    TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extensive collection of customizable neural layers to build advanced AI models quickly, based on this, the community open-sourced mass tutorials and applications. TensorLayer is awarded the 2017 Best Open Source Software by the ACM Multimedia Society. This project can also be found at OpenI and Gitee. 3.0.0 has been pre-released, the current version...
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  • 8
    onnxt5

    onnxt5

    Summarization, translation, sentiment-analysis, text-generation, etc.

    Summarization, translation, sentiment analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in the alpha stage, therefore some functionalities such as beam searches are still in development. The simplest way to get started for generation is to use the default pre-trained version of T5 on ONNX included in the package. Please note that the first time you call get_encoder_decoder_tokenizer, the models are being downloaded which might...
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  • 9
    lxspider

    lxspider

    Educational Python web scraping case collection for many sites

    lxSpider is a collection of web scraping examples designed primarily for learning and experimentation with data extraction techniques. It gathers numerous crawler implementations that demonstrate how to collect data from a wide range of websites and online services. It focuses heavily on practical cases that illustrate how different platforms handle requests, authentication parameters, and anti-scraping protections. lxSpider includes examples targeting areas such as e-commerce platforms,...
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  • 10
    Awesome AI-ML-DL

    Awesome AI-ML-DL

    Awesome Artificial Intelligence, Machine Learning and Deep Learning

    Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics. This repo is dedicated to engineers, developers, data scientists and all other professions that take interest in AI, ML, DL and related sciences. To make learning interesting and to create a place to easily find all the necessary material. Please contribute, watch, star, fork and share the repo with others in your community.
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  • 11
    Ad-papers

    Ad-papers

    Papers on Computational Advertising

    The Ad-papers repository is a curated collection of influential research papers focused on the fields of advertising technology, recommendation systems, and applied machine learning in online platforms. The repository organizes academic and industry papers that explore how machine learning algorithms can be used to improve ad targeting, user modeling, click-through rate prediction, and personalized recommendation systems. These papers represent key developments in large-scale industrial...
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  • 12
    transferlearning-tutorial

    transferlearning-tutorial

    Tutorial on applied transfer learning

    A bilingual (English/Chinese) concise tutorial on applied transfer learning, hosted by Jindong Wang. It includes LaTeX source for a compact handbook covering theory, algorithms, surveys, and code in MATLAB and Python.
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  • 13
    Vector AI

    Vector AI

    A platform for building vector based applications

    Vector AI is a framework designed to make the process of building production-grade vector-based applications as quick and easily as possible. Create, store, manipulate, search and analyze vectors alongside json documents to power applications such as neural search, semantic search, personalized recommendations etc. Image2Vec, Audio2Vec, etc (Any data can be turned into vectors through machine learning). Store your vectors alongside documents without having to do a db lookup for metadata...
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  • 14
    Tabnine

    Tabnine

    Vim client for TabNine

    Tabnine is an AI-powered code completion extension trusted by millions of developers around the world. Whether you’re just getting started as a developer or if you’ve been doing it for decades, Tabnine will help you code twice as fast with half the keystrokes – all in your favorite IDE. Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, or...
    Downloads: 8 This Week
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  • 15
    Text2Video

    Text2Video

    Software tool that converts text to video for more engaging experience

    ...I created a prototype web application that takes text as an input and generates a video as an output. I plan to further work on the project targeting young college students who are aged between 18 to 23 because they tend to prefer learning through videos over books based on the survey I found. The technologies I used for the project are HTML, CSS, Javascript, Node.js, CCapture.js, ffmpegserver.js, Amazon Polly, Python, Flask, gevent, spaCy, and Pixabay API.
    Downloads: 2 This Week
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  • 16
    ALAE

    ALAE

    Adversarial Latent Autoencoders

    ALAE (Adversarial Latent Autoencoders) is a deep learning research implementation that combines autoencoders with generative adversarial networks to produce high-quality image synthesis models. The project implements the architecture introduced in the CVPR research paper on Adversarial Latent Autoencoders, which focuses on improving generative modeling by learning latent representations aligned with adversarial training objectives. Unlike traditional GANs that directly generate images from...
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  • 17
    Surface Defect Detection Dataset Papers

    Surface Defect Detection Dataset Papers

    Constantly summarizing open source dataset and critical papers

    At present, surface defect equipment based on machine vision has widely replaced artificial visual inspection in various industrial fields, including 3C, automobiles, home appliances, machinery manufacturing, semiconductors and electronics, chemical, pharmaceutical, aerospace, light industry and other industries. Traditional surface defect detection methods based on machine vision often use conventional image processing algorithms or artificially designed features plus classifiers. Generally...
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  • 18
    Libra

    Libra

    Ergonomic machine learning for everyone

    An ergonomic machine learning library for non-technical users. Save time. Blaze through ML.
    Downloads: 1 This Week
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  • 19
    NLP Architect

    NLP Architect

    A model library for exploring state-of-the-art deep learning

    NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. ...
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  • 20
    gradslam

    gradslam

    gradslam is an open source differentiable dense SLAM library

    gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations...
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  • 21
    TFLearn

    TFLearn

    Deep learning library featuring a higher-level API for TensorFlow

    TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency...
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  • 22
    Lambda Networks

    Lambda Networks

    Implementation of LambdaNetworks, a new approach to image recognition

    Implementation of λ Networks, a new approach to image recognition that reaches SOTA on ImageNet. The new method utilizes λ layer, which captures interactions by transforming contexts into linear functions, termed lambdas, and applying these linear functions to each input separately. Shinel94 has added a Keras implementation! It won't be officially supported in this repository, so either copy / paste the code under ./lambda_networks/tfkeras.py or make sure to install tensorflow and keras...
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  • 23
    Ceka

    Ceka

    Crowd Environment and its Knowledge Analysis

    A knowledge analysis tool for crowdsourcing based on Weka. We also have a Python version of Crowdsourcing Learning: CrowdwiseKit on GitHub (https://github.com/tssai-lab/CrowdwiseKit).
    Downloads: 0 This Week
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  • 24
    GIMP ML

    GIMP ML

    AI for GNU Image Manipulation Program

    This repository introduces GIMP3-ML, a set of Python plugins for the widely popular GNU Image Manipulation Program (GIMP). It enables the use of recent advances in computer vision to the conventional image editing pipeline. Applications from deep learning such as monocular depth estimation, semantic segmentation, mask generative adversarial networks, image super-resolution, de-noising and coloring have been incorporated with GIMP through Python-based plugins. ...
    Downloads: 8 This Week
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  • 25
    OpenAI Glow

    OpenAI Glow

    Copy code in "Glow: Generative Flow with Invertible 1x1 Convolutions"

    Glow is an open source generative model released by OpenAI that demonstrates flow-based generative modeling techniques. Unlike models that rely on approximate inference, Glow uses invertible transformations to directly learn the data distribution, allowing for exact likelihood computation and efficient sampling. The model is capable of producing high-quality synthetic images while maintaining interpretable latent spaces that enable meaningful manipulation of generated outputs. Glow’s...
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