Showing 7 open source projects for "codeigniter social network"

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  • 1
    Spektral

    Spektral

    Graph Neural Networks with Keras and Tensorflow 2

    ...The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs. Spektral implements some of the most popular layers for graph deep learning. Spektral also includes lots of utilities for representing, manipulating, and transforming graphs in your graph deep learning projects. ...
    Downloads: 0 This Week
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  • 2
    Pattern

    Pattern

    Web mining module for Python, with tools for scraping

    Pattern is an open-source Python library that provides tools for web mining, natural language processing, machine learning, and network analysis. The project integrates multiple capabilities into a single framework that allows developers to collect, process, and analyze textual data from the web. It includes modules for web scraping and crawling that can retrieve information from sources such as social media platforms, search engines, and online knowledge bases.
    Downloads: 0 This Week
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  • 3
    Euler

    Euler

    A distributed graph deep learning framework.

    ...Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle.
    Downloads: 2 This Week
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  • 4
    bulbea

    bulbea

    Deep Learning based Python Library for Stock Market Prediction

    ...The library provides tools for retrieving financial time series data, preprocessing market data, and training predictive models that estimate future price movements. bulbea integrates common machine learning frameworks such as TensorFlow and Keras to build neural network models capable of learning patterns in historical financial data. It includes utilities for splitting datasets, normalizing time series, and training models such as recurrent neural networks that can capture temporal dependencies in market behavior. The library also incorporates sentiment analysis capabilities that analyze social media data, particularly from Twitter, to estimate public sentiment toward financial assets.
    Downloads: 0 This Week
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  • 5
    This project aims to develop a method to identify communities in a social network according to some point of view.
    Downloads: 0 This Week
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  • 6
    NeuroKiwi is the application of the Associative Model (AM, previously dubbed AMDroid), being a model storing relational change-detections. The application tries to emulate ground-up knowledge accumulation with limited or no prior knowledge of shapes or patterns.
    Downloads: 0 This Week
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  • 7
    Spider that recollects data from MySpace Social Network. At now, it is only designed to extract information from native american people because it is used for a social science study in the UNAM (Universidad Nacional Autónoma de México).
    Downloads: 0 This Week
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