Search Results for "machine learning python" - Page 81

Showing 3051 open source projects for "machine learning python"

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  • 1
    NLP-progress

    NLP-progress

    Repository to track the progress in Natural Language Processing (NLP)

    Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks. This document aims to track the progress in Natural Language Processing (NLP) and give an overview of the state-of-the-art (SOTA) across the most common NLP tasks and their corresponding datasets. It aims to cover both traditional and core NLP tasks such as dependency parsing and part-of-speech tagging as well as more recent ones such...
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  • 2
    fastText

    fastText

    Library for fast text classification and representation

    ...Such categories can be review scores, spam v.s. non-spam, or the language in which the document was typed. Nowadays, the dominant approach to build such classifiers is machine learning, that is learning classification rules from examples. In order to build such classifiers, we need labeled data, which consists of documents and their corresponding categories (or tags, or labels).
    Downloads: 0 This Week
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  • 3
    Deep-Learning-for-Recommendation-Systems

    Deep-Learning-for-Recommendation-Systems

    This repository contains Deep Learning based articles

    Deep-Learning-for-Recommendation-Systems is a curated repository that aggregates research papers, articles, and code related to deep learning methods for recommender systems. The project organizes influential academic work covering topics such as collaborative filtering, neural recommendation models, and deep feature learning. It includes references to papers describing architectures like collaborative deep learning, neural autoregressive models, and convolutional approaches to...
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  • 4
    ChainerRL

    ChainerRL

    ChainerRL is a deep reinforcement learning library

    ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. ...
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  • 5
    CrypTen

    CrypTen

    A framework for Privacy Preserving Machine Learning

    CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic differentiation and neural network operations. ...
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  • 6
    RL-Stock

    RL-Stock

    Automated stock trading through a simulated training environment

    RL-Stock is a reinforcement learning project that explores automated stock trading through a simulated training environment. It is written as an educational experiment rather than a financial product or investment recommendation system. The project includes scripts for collecting stock data, defining a reinforcement learning environment, training an agent, and visualizing results. It focuses on how an agent can learn trading-like behavior through rewards, states, and actions. The repository...
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  • 7
    MADDPG

    MADDPG

    Code for the MADDPG algorithm from a paper

    MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in...
    Downloads: 2 This Week
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  • 8
    DeepFaceLab

    DeepFaceLab

    The leading software for creating deepfakes

    DeepFaceLab is currently the world's leading software for creating deepfakes, with over 95% of deepfake videos created with DeepFaceLab. DeepFaceLab is an open-source deepfake system that enables users to swap the faces on images and on video. It offers an imperative and easy-to-use pipeline that even those without a comprehensive understanding of the deep learning framework or model implementation can use; and yet also provides a flexible and loose coupling structure for those who want to...
    Downloads: 86 This Week
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  • 9
    imgaug

    imgaug

    Image augmentation for machine learning experiments

    imgaug is a library for image augmentation in machine learning experiments. It supports a wide range of augmentation techniques, allows to easily combine these and to execute them in random order or on multiple CPU cores, has a simple yet powerful stochastic interface and can not only augment images but also key points/landmarks, bounding boxes, heatmaps and segmentation maps. Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions, hue/saturation changes, cropping/padding, blurring, etc. ...
    Downloads: 1 This Week
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  • 10
    Java Neural Network Framework Neuroph
    Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
    Downloads: 28 This Week
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  • 11
    RL Baselines Zoo

    RL Baselines Zoo

    A collection of 100+ pre-trained RL agents using Stable Baselines

    RL Baselines Zoo is a comprehensive training framework and collection of pre-trained RL agents using Stable-Baselines3. It offers tools for training, tuning, and evaluating RL algorithms across many standard environments, including MuJoCo, Atari, and robotics simulations. Designed for reproducible RL research and benchmarking, it includes scripts, hyperparameter presets, and best practices for training robust agents.
    Downloads: 0 This Week
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  • 12
    Olivia

    Olivia

    Your new best friend powered by an artificial neural network

    Olivia is an open-source chatbot built in Golang using Machine Learning technologies. Its goal is to provide a free and open-source alternative to big services like DialogFlow. You can chat with her by speaking (STT) or writing, she replies with a text message but you can enable her voice (TTS). Olivia can listen to you by saying “Hey Olivia” or clicking on the central button. She speaks to reply to you unless you've disabled her voice.
    Downloads: 2 This Week
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  • 13
    TensorWatch

    TensorWatch

    Debugging, monitoring and visualization for Python Machine Learning

    TensorWatch is an open source debugging and visualization platform created by Microsoft Research to support machine learning, deep learning, and reinforcement learning workflows. It enables developers to observe training behavior in real time through interactive visualizations, primarily within Jupyter Notebook environments. The tool treats most data interactions as streams, allowing flexible routing, storage, and visualization of metrics generated during model training. ...
    Downloads: 0 This Week
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  • 14
    Spinning Up in Deep RL

    Spinning Up in Deep RL

    Educational resource to help anyone learn deep reinforcement learning

    Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the development of powerful AI technology. ...
    Downloads: 0 This Week
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  • 15

    FastoCloud PRO

    IPTV/NVR/CCTV/Video cloud https://fastocloud.com

    IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch ...
    Downloads: 4 This Week
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  • 16

    TurboGP

    Genetic Programming library in Python

    TurboGP is a Genetic Programming library written entirely in Python, primarily aimed at Machine Learning tasks. Currently being developed, and in beta version. Lino Rodriguez-Coayahuitl et al. 2020
    Downloads: 0 This Week
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  • 17
    awesome-TS-anomaly-detection

    awesome-TS-anomaly-detection

    List of tools & datasets for anomaly detection on time-series data

    All lists are in alphabetical order. In the lists, maintained projects are prioritized vs not mantained. A repository is considered "not maintained" if the latest commit is > 1 year old, or explicitly mentioned by the authors.
    Downloads: 0 This Week
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  • 18

    Network Manager Control

    A network manager control for OpenBSD

    Nmctl a small python script that allow you to manage your network connections on an OpenBSD machine. Typically you can switch, in one click, from a wifi, to cable, to an another wifi, .... You can even ask nmctl to establish automatically the most approprate connection for you.
    Downloads: 1 This Week
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  • 19
    The Neural Process Family

    The Neural Process Family

    This repository contains notebook implementations

    Neural Processes (NPs) is a collection of interactive Jupyter/Colab notebook implementations developed by Google DeepMind, showcasing three foundational probabilistic machine learning models: Conditional Neural Processes (CNPs), Neural Processes (NPs), and Attentive Neural Processes (ANPs). These models combine the strengths of neural networks and stochastic processes, allowing for flexible function approximation with uncertainty estimation. They can learn distributions over functions from data and efficiently make predictions at new inputs with calibrated uncertainty — making them useful for few-shot learning, Bayesian regression, and meta-learning. ...
    Downloads: 0 This Week
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  • 20
    BytePS

    BytePS

    A high performance and generic framework for distributed DNN training

    BytePS is a high-performance and generally distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on either TCP or RDMA networks. BytePS outperforms existing open-sourced distributed training frameworks by a large margin. For example, on BERT-large training, BytePS can achieve ~90% scaling efficiency with 256 GPUs (see below), which is much higher than Horovod+NCCL. In certain scenarios, BytePS can double the training speed compared with Horovod+NCCL....
    Downloads: 0 This Week
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  • 21
    PyHubs

    PyHubs

    Hubness-aware machine learning in Python

    PyHubs is a machine learning library developed in Python containing implementations of hubness-aware machine learning algorithms together with some useful tools for machine learning experiments. According to our recent observation, old versions of PyHubs (such as 1.2.1) does not provide correct results with new versions of numpy (such as 1.16), however, we think that the most recent version of PyHubs (1.3) works correctly with new versions of numpy as well.
    Downloads: 0 This Week
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  • 22
    A.I. Stock Trends With WEKA & TA-Lib

    A.I. Stock Trends With WEKA & TA-Lib

    A Repository Of The Java Programs Presented in the Videos.

    This is the open/public source code repository for the Java programs shown in the YouTube videos - A.I. Stock Trends With WEKA, TA-Lib and more https://www.youtube.com/channel/UCPxmgFZDS7F06UBBxH5b4mg
    Downloads: 0 This Week
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  • 23
    Weld

    Weld

    High-performance runtime for data analytics applications

    ...Instead of optimizing individual functions independently, Weld introduces an intermediate representation that allows different frameworks to share optimization opportunities. This approach reduces data movement between libraries and enables the system to generate highly optimized machine code for parallel execution. Weld is particularly useful for workloads involving large-scale data processing in frameworks such as NumPy, Spark, and TensorFlow. The language includes built-in constructs for expressing data-parallel operations, enabling efficient execution on modern hardware architectures. By combining operations from multiple libraries into a single optimized execution plan, Weld can significantly improve performance in analytics and machine learning pipelines.
    Downloads: 0 This Week
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  • 24
    Literature of Deep Learning for Graphs

    Literature of Deep Learning for Graphs

    A comprehensive collection of recent papers on graph deep learning

    Literature of Deep Learning for Graphs is a curated repository that collects research papers and educational resources related to deep learning methods for graph-structured data. The project organizes important academic work covering topics such as graph neural networks, graph embeddings, knowledge graphs, and network representation learning. By structuring the literature into categories, the repository allows researchers to quickly identify influential papers in specific subfields of graph machine learning.
    Downloads: 0 This Week
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  • 25
    MMSkeleton

    MMSkeleton

    A OpenMMLAB toolbox for human pose estimation, skeleton-based action

    MMSkeleton is an open-source toolbox for skeleton-based human understanding. It is a part of the open-mmlab project in the charge of Multimedia Laboratory, CUHK. MMSkeleton is developed on our research project ST-GCN. MMSkeleton provides a flexible framework for organizing codes and projects systematically, with the ability to extend to various tasks and scale up to complex deep models. MMSkeleton addresses to multiple tasks in human understanding. Build a custom skeleton-based dataset....
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