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Showing 2239 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"
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Marketing automation for any business | ActiveCampaignActive Intelligence revolutionizes how you work. You guide direction while AI handles execution, acts on insights, and shows you the path forward. It's how marketing should be.
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VoiceShot API - PHP SDK
PHP SDK for processing phone calls and SMS through the VoiceShot API.
VoiceShot's API allows you to quickly integrate both incoming and outgoing phone calling and text messaging services into your applications. From your own applications, you can easily place and receive interactive telephone calls and text messages. Put callers in touch with the data and people they want when they want it. Send notification phone calls and text messages, automate customer service calls/texts, provide order status and integrate with your own custom applications to provide services customized to your needs. Improve your business's efficiency and enhance your image. -
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VoiceShot API - .NET SDK
.NET SDK for processing phone calls and SMS through the VoiceShot API.
VoiceShot's API allows you to quickly integrate both incoming and outgoing phone calling and text messaging services into your applications. From your own applications, you can easily place and receive interactive telephone calls and text messages. Put callers in touch with the data and people they want when they want it. Send notification phone calls and text messages, automate customer service calls/texts, provide order status and integrate with your own custom applications to provide services customized to your needs. Improve your business's efficiency and enhance your image. -
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VoiceShot API - ASP SDK
ASP SDK for processing phone calls and SMS through the VoiceShot API.
VoiceShot's API allows you to quickly integrate both incoming and outgoing phone calling and text messaging services into your applications. From your own applications, you can easily place and receive interactive telephone calls and text messages. Put callers in touch with the data and people they want when they want it. Send notification phone calls and text messages, automate customer service calls/texts, provide order status and integrate with your own custom applications to provide services customized to your needs. Improve your business's efficiency and enhance your image. -
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PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
Secure Cloud Storage for Files, Photos and Documents | pCloudStore, sync, and share your files securely with pCloud. Get up to 10 GB of free secure cloud storage and access your files from any device, anywhere.
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5
EverydayWechat
Python tool that automates WeChat messages, replies, & group utilities
...In addition to personal messaging automation, the project includes a group assistant that can respond to queries and provide useful information within chat groups. These group utilities can retrieve data such as weather conditions, calendar details, garbage classification information, movie box office statistics, delivery tracking updates, and air quality reports. -
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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. ... -
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TensorFlow Machine Learning Cookbook
Code for Tensorflow Machine Learning Cookbook
...The repository contains numerous Python scripts and Jupyter notebooks that demonstrate how to implement machine learning algorithms and neural networks using the TensorFlow framework. Each section focuses on a different aspect of machine learning development, including tensor manipulation, model training, optimization strategies, and data processing techniques. The examples illustrate how TensorFlow operations and tensors can be used to build machine learning pipelines and perform tasks such as regression, classification, and clustering. By combining theoretical explanations with executable code, the project helps developers understand how TensorFlow algorithms operate internally while also providing working examples that can be adapted for real projects. -
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rpackage conjurer
Synthetic data generation using R
Builds synthetic data applicable across multiple domains. This package also provides flexibility to control data distribution to make it relevant to many industry examples. -
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Python Machine Learning
The "Python Machine Learning (2nd edition)" book code repository
...The structure also includes errata documentation and assets (images) that appear in the printed edition, providing a rich supplement to learning. The repository is suitable both for classroom use and for self-study, as well as being a go-to reference for data scientists revisiting techniques. -
Gearset | The complete Salesforce DevOps solutionGearset is the only platform you need for unparalleled deployment success, continuous delivery, automated testing and backups.
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KSUCCA Corpus
A 50 million tokens corpus of Classical Arabic.
King Saud University Corpus of Classical Arabic (KSUCCA) is a pioneering 50 million tokens annotated corpus of Classical Arabic texts from the period of pre-Islamic era until the fourth Hijri century (equivalent to the period from the seventh until early eleventh century CE), which is the period of pure classical Arabic. The main aim of this corpus is to be used for studying the distributional lexical semantics of The Quran words. However, it can be used for other research purposes, such... -
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Dive-into-DL-TensorFlow2.0
Dive into Deep Learning
...In addition, this project also refers to the project Dive-into-DL-PyTorch , which refactored PyTorch in the Chinese version of this book, and I would like to express my gratitude here. This repository mainly contains two folders, code and docs (plus some data stored in data). The code folder is the relevant jupyter notebook code for each chapter (based on TensorFlow2); the docs folder is the relevant content in the book. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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Phenalysis
Analyze agronomic plant research plots in aerial orthomosaic images.
A graphical user interface to import, analyze and export plots from orthomosaic images of agronomic trials. Please cite the following reference in your work if you use Phenalysis: Khan Z and Miklavcic SJ (2019) An Automatic Field Plot Extraction Method From Aerial Orthomosaic Images. Front. Plant Sci. 10:683. doi: https://doi.org/10.3389/fpls.2019.00683 This tool is being developed through the sponsorship of the Australian Research Council's Industrial Transformation Research Hub on... -
14
Ai-chan
A simple chat bot written in Python.
Ai-chan is a chat bot you can run offline. You can teach her new conversations, share her memory data, change her appearance, her name, the way she calls you, etc. -
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Deep Learning with PyTorch
Latest techniques in deep learning and representation learning
This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course. To be able to follow the exercises, you are going to need a laptop with Miniconda (a minimal version of Anaconda) and several Python packages installed. The following instruction would work as is for Mac or Ubuntu Linux users, Windows users would need to install and work in the Git BASH terminal. ... -
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Image Quality Assessment
Convolutional Neural Networks to predict aesthetic quality of images
...The repository includes code for training models, performing inference, and evaluating predicted scores against labeled datasets. It also provides utilities for image preprocessing and data management that help prepare datasets for training deep learning models. -
17
CCZero (中国象棋Zero)
Implement AlphaZero/AlphaGo Zero methods on Chinese chess
ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics. -
18
gpt2-client
Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.
...It features a Transformer model that was brought to light by the Attention Is All You Need paper in 2017. The model has 4 versions - 124M, 345M, 774M, and 1558M - that differ in terms of the amount of training data fed to it and the number of parameters they contain. Finally, gpt2-client is a wrapper around the original gpt-2 repository that features the same functionality but with more accessiblity, comprehensibility, and utilty. You can play around with all four GPT-2 models in less than five lines of code. Install client via pip. The generation options are highly flexible. ... -
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AI Cheatsheets
Essential Cheat Sheets for deep learning and machine learning research
cheatsheets-ai is an open-source repository that collects essential cheat sheets covering many tools and concepts used in machine learning, deep learning, and data science. The project aims to provide quick-reference materials that help engineers, researchers, and students review key techniques and frameworks without reading extensive documentation. It compiles cheat sheets for widely used libraries and technologies such as TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Matplotlib, and PySpark. ... -
20
MatchZoo
Facilitating the design, comparison and sharing of deep text models
...Generate pair-wise training data on-the-fly, evaluate model performance using customized callbacks on validation data. MatchZoo is dependent on Keras and Tensorflow. -
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Chatito
Dataset generation for AI chatbots, NLP tasks
Chatito is a tool that helps generate datasets for training and validating chatbot models using a simple domain-specific language (DSL). -
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Docker Machine
Machine management for a container-centric world
Docker Machine is a tool that lets you install Docker Engine on virtual hosts, and manage the hosts with docker-machine commands. You can use Machine to create Docker hosts on your local Mac or Windows box, on your company network, in your data center, or on cloud providers like Azure, AWS, or DigitalOcean. Using docker-machine commands, you can start, inspect, stop, and restart a managed host, upgrade the Docker client and daemon, and configure a Docker client to talk to your host. Point the Machine CLI at a running, managed host, and you can run docker commands directly on that host. ... -
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PyTorch-BigGraph
Generate embeddings from large-scale graph-structured data
PyTorch-BigGraph (PBG) is a system for learning embeddings on massive graphs—think billions of nodes and edges—using partitioning and distributed training to keep memory and compute tractable. It shards entities into partitions and buckets edges so that each training pass only touches a small slice of parameters, which drastically reduces peak RAM and enables horizontal scaling across machines. PBG supports multi-relation graphs (knowledge graphs) with relation-specific scoring functions,... -
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NiftyNet
An open-source convolutional neural networks platform for research
...NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging data. Quickly build new solutions to your own image analysis problems. NiftyNet currently supports medical image segmentation and generative adversarial networks. NiftyNet is not intended for clinical use. -
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X-DeepLearning
An industrial deep learning framework for high-dimension sparse data
X-DeepLearning (XDL for short) is a complete set of deep optimization solutions for high-dimensional sparse data scenarios (such as advertising/recommendation/search, etc.). XDL version 1.2 has been released recently. Performance optimization for large batch/low concurrency scenarios, 50-100% performance improvement in such scenarios. Storage and communication optimization, parameters are automatically allocated globally without manual intervention, and requests are merged to completely eliminate computing/storage/communication hotspots of ps. ...
