Showing 3 open source projects for "node"

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    AestheticsPro Medical Spa Software

    Our new software release will dramatically improve your medspa business performance while enhancing the customer experience

    AestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
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  • The Most Powerful Software Platform for EHSQ and ESG Management Icon
    The Most Powerful Software Platform for EHSQ and ESG Management

    Addresses the needs of small businesses and large global organizations with thousands of users in multiple locations.

    Choose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
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  • 1
    Waves Platform Node

    Waves Platform Node

    Host connected to the Waves blockchain network

    Waves Platform Node is a host connected to the Waves blockchain network. Waves is an open source blockchain platform that offers a full blockchain ecosystem for building decentralised applications. Nodes are its critical components, performing several important functions such as processing and validating transactions, and generating and storing blocks.
    Downloads: 10 This Week
    Last Update:
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  • 2
    Eclair

    Eclair

    A scala implementation of the Lightning Network

    ...If you are upgrading an existing wallet, you may need to create a new address and send all your funds to that address. Eclair needs a synchronized, segwit-ready, zeromq-enabled, wallet-enabled, non-pruning, tx-indexing Bitcoin Core node. You must configure your Bitcoin node to use bech32 (segwit) addresses.
    Downloads: 0 This Week
    Last Update:
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  • 3
    node2vec

    node2vec

    Learn continuous vector embeddings for nodes in a graph using biased R

    The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction....
    Downloads: 1 This Week
    Last Update:
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