Showing 4 open source projects for "organic"

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    Robyn

    Robyn

    Experimental, AI/ML-powered and open sourced Marketing Mix Modeling

    ...Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of techniques, regularized regression (Ridge), time-series decomposition (trend, seasonality, holiday effects), and hyperparameter optimization (via evolutionary algorithms), to estimate the incremental impact of each marketing channel. It explicitly models “carry-over” (adstock) and diminishing-returns (saturation) effects per channel, enabling realistic modeling of how advertising persists over time and saturates.
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  • 2

    CRP - Chemical Reaction Prediction

    Predicting Organic Reactions using Neural Networks.

    The intend is to solve the forward-reaction prediction problem, where the reactants are known and the interest is in generating the reaction products using Deep learning. This Graphical User Interface takes simplified molecular-input line-entry system (SMILES) as an input and generates the product SMILE & molecule. Beam search is used in Version 2, to generate top 5 predictions. Maximum input length for the model is 15 (excluding spaces).
    Downloads: 0 This Week
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  • 3

    CoffeeMud For AI

    CoffeeMudForAI is plaform to design AI in

    ...Think World of Warcraft(or any other massively multiplayer online game) but text based. AI or artificial intelligence is the field that is interested in the creation of non-organic intelligence. Mud AI platform goals 1. To provide a platform for AI research that has robotic-like sensory limitations but doesn't actually require robotics. 2. To provide a platform for undergraduate computer scientists to build relatively complex AI. 3. To provide a set of agents that non-technical people can play around with and get a feel for how various AI techniques work. ...
    Downloads: 0 This Week
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  • 4
    TreeLiker

    TreeLiker

    TreeLiker is a collection of fast algorithms for working with complex

    TreeLiker is a collection of fast algorithms for working with complex structured data in relational form. The data can, for example, describe large organic molecules such as proteins or groups of individuals such as social networks or predator-prey networks etc. The algorithms included in TreeLiker are unique in that, in principle, they are able to search given sets of relational patterns exhaustively, thus guaranteeing that if some good pattern capturing an important feature of the problem exists, it will be found. ...
    Downloads: 0 This Week
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