Showing 215 open source projects for "python q learning"

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  • 1
    Alpa

    Alpa

    Training and serving large-scale neural networks

    Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code.
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  • 2
    HydraDragonAntivirus

    HydraDragonAntivirus

    Dynamic and static analysis with Sandboxie for Windows, including EDR

    Dynamic and static analysis with Sandboxie for Windows, including EDR, ClamAV, YARA-X, custom machine learning AI, behavioral analysis, NLP-based detection, website signatures, Ghidra, Suricata, Sigma, and much more than you can imagine
    Downloads: 8 This Week
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  • 3

    Taylorplot_Neptune

    Creation of a Taylorplot for several machine learning models

    Here we present the lines of code for creating a taylor plot with python to display several machine learning models. We show the solution for displaying 10 models, but the list and number can be changed simply by modifying the sample list.
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  • 4
    AStro inFER - a rule miner and executer
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    MongoDB Atlas runs apps anywhere

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  • 5
    Zylthra

    Zylthra

    Zylthra: A PyQt6 app to generate synthetic datasets with DataLLM.

    Welcome to Zylthra, a powerful Python-based desktop application built with PyQt6, designed to generate synthetic datasets using the DataLLM API from data.mostly.ai. This tool allows users to create custom datasets by defining columns, configuring generation parameters, and saving setups for reuse, all within a sleek, dark-themed interface.
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  • 6
    Solver
    Forget about sleepless nights over textbooks! Solver is an application that solves equations quickly and easily. • Solve equations of any type — from linear to the fourth degree. • Save time and effort — you won't have to learn anything else. • Import and export data — work with equations from files and save solutions in the desired format. Don't miss the chance to make learning math simple and effective!
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  • 7
    pipeless

    pipeless

    A computer vision framework to create and deploy apps in minutes

    Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new...
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  • 8
    MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
    Downloads: 0 This Week
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  • 9
    Neural Network Visualization

    Neural Network Visualization

    Project for processing neural networks and rendering to gain insights

    nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase...
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  • No-Nonsense Code-to-Cloud Security for Devs | Aikido Icon
    No-Nonsense Code-to-Cloud Security for Devs | Aikido

    Connect your GitHub, GitLab, Bitbucket, or Azure DevOps account to start scanning your repos for free.

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  • 10
    UnionML

    UnionML

    Build and deploy machine learning microservices

    Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine...
    Downloads: 0 This Week
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  • 11
    Petastorm

    Petastorm

    Petastorm library enables single machine or distributed training

    Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular...
    Downloads: 0 This Week
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  • 12
    AI-Agent-Host

    AI-Agent-Host

    The AI Agent Host is a module-based development environment.

    The AI Agent Host integrates several advanced technologies and offers a unique combination of features for the development of language model-driven applications. The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI...
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  • 13
    Twinify

    Twinify

    Privacy-preserving generation of a synthetic twin to a data set

    twinify is a software package for the privacy-preserving generation of a synthetic twin to a given sensitive tabular data set. On a high level, twinify follows the differentially private data-sharing process introduced by Jälkö et al.. Depending on the nature of your data, twinify implements either the NAPSU-MQ approach described by Räisä et al. or finds an approximate parameter posterior for any probabilistic model you formulated using differentially private variational inference (DPVI)....
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  • 14
    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...
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  • 15
    PyTorch Transfer-Learning-Library

    PyTorch Transfer-Learning-Library

    Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.

    TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please...
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  • 16
    GFPGAN

    GFPGAN

    GFPGAN aims at developing Practical Algorithms

    GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. Colab Demo for GFPGAN; (Another Colab Demo for the original paper model) Online demo: Huggingface (return only the cropped face) Online demo: Replicate.ai (may need to sign in, return the whole image). Online demo: Baseten.co (backed by GPU, returns the whole image). We provide a clean version of GFPGAN, which can run without CUDA extensions. So that it can run in Windows or on CPU mode. GFPGAN aims at developing...
    Downloads: 79 This Week
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  • 17
    DeepCTR-Torch

    DeepCTR-Torch

    Easy-to-use,Modular and Extendible package of deep-learning models

    DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical...
    Downloads: 0 This Week
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  • 18
    Gym

    Gym

    Toolkit for developing and comparing reinforcement learning algorithms

    Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no assumptions...
    Downloads: 0 This Week
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  • 19
    BEVFormer

    BEVFormer

    Implementation of BEVFormer, a camera-only framework

    3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV...
    Downloads: 0 This Week
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  • 20
    Fairseq

    Fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python

    Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the...
    Downloads: 1 This Week
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  • 21
    SageMaker MXNet Inference Toolkit

    SageMaker MXNet Inference Toolkit

    Toolkit for allowing inference and serving with MXNet in SageMaker

    SageMaker MXNet Inference Toolkit is an open-source library for serving MXNet models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain MXNet model types and utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning...
    Downloads: 0 This Week
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  • 22
    Apache MXNet (incubating)

    Apache MXNet (incubating)

    A flexible and efficient library for deep learning

    Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable.
    Downloads: 0 This Week
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  • 23
    OpenPrompt

    OpenPrompt

    An Open-Source Framework for Prompt-Learning

    Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. OpenPrompt is a library built upon PyTorch and provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other...
    Downloads: 0 This Week
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  • 24
    q - Text as Data

    q - Text as Data

    Run SQL directly on CSV or TSV files

    q is a command line tool that allows direct execution of SQL-like queries on CSVs/TSVs (and any other tabular text files). q treats ordinary files as database tables, and supports all SQL constructs, such as WHERE, GROUP BY, JOINs etc. It supports automatic column name and column type detection, and provides full support for multiple encodings. q fully supports all types of encoding. Use -e data-encoding to set the input data encoding, -Q query-encoding to set the query encoding, and use -E...
    Downloads: 0 This Week
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  • 25
    Deep Daze

    Deep Daze

    Simple command line tool for text to image generation

    Simple command-line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). In true deep learning fashion, more layers will yield better results. Default is at 16, but can be increased to 32 depending on your resources. Technique first devised and shared by Mario Klingemann, it allows you to prime the generator network with a starting image, before being steered towards the text. Simply specify the path to the image you wish to use...
    Downloads: 1 This Week
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