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Refactor index.html for improved structure and content
Updated the HTML structure and added missing content.
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‎index.html‎

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<!doctype html>
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<html>
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<head>
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<meta charset="utf-8">
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<meta charset="utf-8">
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<title>Techtonique/Packages</title>
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<meta http-equiv="X-UA-Compatible" content="IE=edge" />
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<!-- spacelab litera sandstone cyborg slate -->
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<link rel="stylesheet" href="https://bootswatch.com/4/darkly/bootstrap.css" media="screen">
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<link rel="stylesheet" href="https://bootswatch.com/_assets/css/custom.min.css">
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<link rel="icon" type="image/png" href="images/t-logo.png">
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<!-- Global site tag (gtag.js) - Google Analytics -->
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<script async src="https://www.googletagmanager.com/gtag/js?id=UA-146345113-2">
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</script>
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<script>
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window.dataLayer = window.dataLayer || [];
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function gtag(){dataLayer.push(arguments);}
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gtag('js', new Date());
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gtag('config', 'UA-146345113-2');
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</script>
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</head>
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<body>
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<div class="navbar navbar-expand-lg fixed-top navbar-dark bg-dark">
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<!-- NAVBAR -->
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<div class="navbar navbar-expand-lg fixed-top navbar-dark bg-dark">
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<div class="container">
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<a href="/" class="navbar-brand">Techtonique</a>
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<button class="navbar-toggler" type="button" data-toggle="collapse"
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data-target="#navbarResponsive" aria-controls="navbarResponsive" aria-expanded="false"
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aria-label="Toggle navigation">
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data-target="#navbarResponsive">
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<span class="navbar-toggler-icon"></span>
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</button>
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<div class="collapse navbar-collapse" id="navbarResponsive" style="">
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<div class="collapse navbar-collapse" id="navbarResponsive">
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<ul class="navbar-nav">
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<li class="nav-item">
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<a class="nav-link" href="https://github.com/Techtonique/">GitHub</a>
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</li>
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</li>
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</ul>
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</div>
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<div class="container">
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<div class="container">
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<div class="page-header" id="banner">
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<div class="row">
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<div class="col-lg-8 col-md-7 col-sm-6">
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<h1>Techtonique</h1>
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<p class="lead">Packages</p>
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<br>
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</div>
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<div class="col-lg-4 col-md-5 col-sm-6">
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<div class="sponsor">
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<img src="images/t-logo.png" alt="Logo">
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<!-- <script async type="text/javascript" src="//cdn.carbonads.com/carbon.js?serve=CKYIE23N&placement=bootswatchcom" id="_carbonads_js"></script> -->
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</div>
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<br>
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<br>
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<br><br>
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<div class="container">
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<div class="row">
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<div class="row">
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<div class="bs-component">
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<div class="col-lg-12">
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<p>Welcome to <b>Techtonique/Packages</b>.
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<br>
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<br>
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<b>Techtonique = tech, statistics, machine learning,
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computer simulation, numerical optimization. </b>
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<br>
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Here, you'll find
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<b>examples + documentation</b> for
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<b> <a href="https://github.com/Techtonique">Techtonique</a></b>'s tools.
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<br>
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<br>
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Currently available:
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<ul>
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<li> <a href="nnetsauce/index.html">nnetsauce for Python</a> &nbsp; and <a href="nnetsauce_r/">nnetsauce for R</a> &nbsp; Statistical/Machine Learning using Randomized and Quasi-Randomized (neural) networks &nbsp; | &nbsp; <a href="https://pepy.tech/project/nnetsauce"><img alt="Downloads" src="https://static.pepy.tech/badge/nnetsauce" /></a> <a href="https://anaconda.org/conda-forge/nnetsauce"> <img src="https://anaconda.org/conda-forge/nnetsauce/badges/downloads.svg" /> </a> </li>
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<li> <a href="mlsauce/index.html">mlsauce for Python</a> &nbsp; and &nbsp; <a href="mlsauce_r/index.html">mlsauce for R</a> &nbsp; Miscellaneous Statistical/Machine Learning stuff &nbsp;|&nbsp; <a href="https://pepy.tech/project/mlsauce"><img alt="Downloads" src="https://static.pepy.tech/badge/mlsauce" /></a> <a href="https://anaconda.org/conda-forge/mlsauce"> <img src="https://anaconda.org/conda-forge/mlsauce/badges/downloads.svg" /> </a> </li>
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<li> <a href="ahead/index.html">ahead (for R)</a> &nbsp; and &nbsp; <a href="ahead_python/index.html">ahead (for Python)</a> &nbsp; Univariate and Multivariate time series forecasting &nbsp;|&nbsp; <a href="https://pepy.tech/project/ahead"><img alt="Downloads" src="https://static.pepy.tech/badge/ahead" /></a> <a href="https://anaconda.org/conda-forge/ahead_python"> <img src="https://anaconda.org/conda-forge/ahead_python/badges/downloads.svg" /> </a> </li>
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<li> <a href="GPopt/index.html">gpopt</a> &nbsp; Bayesian optimization using Gaussian Process Regression &nbsp;|&nbsp; <a href="https://pepy.tech/project/gpopt"><img alt="Downloads" src="https://static.pepy.tech/badge/gpopt" /></a> </li>
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<li> <a href="bcn/index.html">bcn (for R)</a> &nbsp; and &nbsp; <a href="bcn_python/index.html">BCN (for Python)</a> &nbsp; Boosted Configuration (neural) Networks for supervised learning &nbsp;|&nbsp; <a href="https://pepy.tech/project/bcn"><img alt="Downloads" src="https://static.pepy.tech/badge/bcn" /></a></li>
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<li> <a href="teller/index.html">teller</a> &nbsp; Model-agnostic Statistical/Machine Learning explainability &nbsp;|&nbsp; <a href="https://pepy.tech/project/the-teller"><img alt="Downloads" src="https://static.pepy.tech/badge/the-teller" /></a> </li>
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<li> <a href="querier/index.html">querier</a> &nbsp; A query language for Python Data Frames &nbsp;|&nbsp; <a href="https://pepy.tech/project/querier"><img alt="Downloads" src="https://static.pepy.tech/badge/querier" /></a> </li>
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<li> <a href="ESGtoolkit/index.html">esgtoolkit</a> &nbsp; A toolkit for Monte Carlo Simulations in Finance, Economics, Insurance, Physics <a href="https://pepy.tech/project/esgtoolkit"><img alt="Downloads" src="https://static.pepy.tech/badge/esgtoolkit" /></a> </li>
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<li> <a href="rtopy/index.html">rtopy</a> &nbsp; Calling R functions in Python &nbsp;|&nbsp; <a href="https://pepy.tech/project/rtopy"><img alt="Downloads" src="https://static.pepy.tech/badge/rtopy" /></a> <a href="https://anaconda.org/conda-forge/rtopy"> <img src="https://anaconda.org/conda-forge/rtopy/badges/downloads.svg" /> </a> </li>
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<li> <a href="crossvalidation/index.html">crossvalidation</a> &nbsp; Generic R functions for cross-validation</li>
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<li> <a href="learningmachine/index.html">learningmachine (for R)</a> &nbsp; and &nbsp; <a href="learningmachine_python/index.html">learningmachine (for Python)</a> Machine Learning with Explanations and Uncertainty Quantification |&nbsp; <a href="https://pepy.tech/project/learningmachine"><img alt="Downloads" src="https://static.pepy.tech/badge/learningmachine" /></a> </li>
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<li> <a href="unifiedbooster/index.html">unifiedbooster</a> &nbsp; Unified interface for Gradient Boosted Decision Trees algorithms |&nbsp; <a href="https://pepy.tech/project/unifiedbooster"><img alt="Downloads" src="https://static.pepy.tech/badge/unifiedbooster" /></a> </li>
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<li> <a href="misc/index.html">misc</a> &nbsp; Miscellaneous useful R functions</li>
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<li> <a href="techtonique_api_py/index.html">Techtonique API calls in Python</a> &nbsp; and &nbsp; <a href="techtonique_api_r/index.html">Techtonique API calls in R</a> &nbsp;|&nbsp; <a href="https://pepy.tech/project/forecastingapi"><img alt="Downloads" src="https://static.pepy.tech/badge/forecastingapi" /></a> </li>
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<li>
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<a href="survivalist/index.html">survivalist</a> &nbsp; Model agnostic Survival analysis with Machine Learning and uncertainty quantification &nbsp;|&nbsp; <a href="https://pepy.tech/project/survivalist"><img alt="Downloads" src="https://static.pepy.tech/badge/survivalist" /></a>
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</li>
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<a href="tisthemachinelearner_r/index.html">tisthemachinelearner (R) </a> &nbsp; <a href="tisthemachinelearner/index.html">tisthemachinelearner (Python) </a> &nbsp; Lightweight interface to scikit-learn with 2 classes, Classifier and Regressor. &nbsp;|&nbsp; <a href="https://pepy.tech/project/tisthemachinelearner"><img alt="Downloads" src="https://static.pepy.tech/badge/tisthemachinelearner" /></a>
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</li>
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<li>
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<a href="genbooster/index.html">genbooster</a> &nbsp; A fast gradient boosting and bagging (RandomBagClassifier, similar to RandomForestClassifier) implementation using Rust and Python. Any base learner can be employed. &nbsp;|&nbsp; <a href="https://pepy.tech/project/genbooster"><img alt="Downloads" src="https://static.pepy.tech/badge/genbooster" /></a>
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</li>
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<a href="matern32/index.html">matern32</a> &nbsp; Interpretable Kernel Ridge Regression using Matern 3/2 kernels in R.
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</li>
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<li>
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<a href="bayesianrvfl/index.html">bayesianrvfl</a> &nbsp; Adaptive Bayesian (NON)Linear regression in R.
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</li>
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<a href="after/index.html">after</a> &nbsp; Univariate and multivariate time series forecasting with multiple models.
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</li>
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<a href="rvfl/index.html">rvfl</a> &nbsp; Random Vector Functional Link (RVFL) networks in R.
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</li>
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<li>
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<a href="mlreserving/index.html">mlreserving</a> &nbsp; Machine Learning Reserving for (longitudinal) triangle data. &nbsp;|&nbsp; <a href="https://pepy.tech/project/mlreserving"><img alt="Downloads" src="https://static.pepy.tech/badge/mlreserving" /></a>
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</li>
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<li>
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<a href="glmnetforpython/index.html">GLMNet</a> &nbsp; Elastic Net regression and classification using GLMNet. &nbsp;|&nbsp; <a href="https://pepy.tech/project/glmnetforpython"><img alt="Downloads" src="https://static.pepy.tech/badge/glmnetforpython" /></a>
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</li>
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<li>
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<a href="cybooster/index.html">cybooster</a> &nbsp; Generic Boosting (can use GPUs). &nbsp;|&nbsp; <a href="https://pepy.tech/project/cybooster"><img alt="Downloads" src="https://static.pepy.tech/badge/cybooster" /></a>
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</li>
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<li>
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<a href="ftsatoo/index.html">ftsatoo</a> &nbsp; Functions for visualizing, modeling, (generic) forecasting and hypothesis testing of functional time series.
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</li>
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<li>
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<a href="stochasticscenarios/index.html">stochasticscenarios</a> A Package for Asset Projection Using Stochastic Simulation
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</li>
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<li>
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<a href="synthe/index.html">synthe</a> Synthetic Data Simulation/Generation |&nbsp; <a href="https://pepy.tech/project/synthe"><img alt="Downloads" src="https://static.pepy.tech/badge/synthe" /></a>
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</li>
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<li>
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<a href="unifiedml/index.html">unifiedml</a> A Unified Machine Learning Interface for R (any R model you can think of)
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</li>
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</ul>
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</p>
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<p>Welcome to <b>Techtonique/Packages</b>.</p>
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<p><b>Techtonique = tech, statistics, machine learning,
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computer simulation, numerical optimization.</b></p>
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<p>Here, you'll find <b>examples + documentation</b> for
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<b><a href="https://github.com/Techtonique">Techtonique</a></b>'s tools.</p>
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<p>Currently available:</p>
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<ul>
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<!-- Python + R packages with added R badges (cranlogs / R-universe) -->
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<li>
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<a href="nnetsauce/index.html">nnetsauce for Python</a> &nbsp; and
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<a href="nnetsauce_r/">nnetsauce for R</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/nnetsauce" />
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| Python: <img src="https://static.pepy.tech/badge/nnetsauce" />
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</li>
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<li>
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<a href="mlsauce/index.html">mlsauce for Python</a> &nbsp; and
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<a href="mlsauce_r/index.html">mlsauce for R</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/mlsauce" />
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| Python: <img src="https://static.pepy.tech/badge/mlsauce" />
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</li>
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<li>
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<a href="ahead/index.html">ahead (R)</a> &nbsp; and &nbsp;
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<a href="ahead_python/index.html">ahead (Python)</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/ahead" />
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| Python: <img src="https://static.pepy.tech/badge/ahead" />
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</li>
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<li>
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<a href="GPopt/index.html">gpopt</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/gpopt" />
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</li>
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<li>
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<a href="bcn/index.html">bcn (R)</a> &nbsp; and &nbsp;
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<a href="bcn_python/index.html">BCN (Python)</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/bcn" />
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| Python: <img src="https://static.pepy.tech/badge/bcn" />
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</li>
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<li>
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<a href="teller/index.html">teller</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/teller" />
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</li>
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<a href="querier/index.html">querier</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/querier" />
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</li>
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<li>
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<a href="ESGtoolkit/index.html">esgtoolkit</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/ESGtoolkit" />
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</li>
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<li>
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<a href="rtopy/index.html">rtopy</a>
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&nbsp; | Python: <img src="https://static.pepy.tech/badge/rtopy" />
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</li>
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<li>
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<a href="crossvalidation/index.html">crossvalidation</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/crossvalidation" />
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</li>
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<li>
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<a href="learningmachine/index.html">learningmachine (R)</a> &nbsp; and
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<a href="learningmachine_python/index.html">learningmachine (Python)</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/learningmachine" />
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</li>
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<li>
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<a href="unifiedbooster/index.html">unifiedbooster</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/unifiedbooster" />
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</li>
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<li>
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<a href="misc/index.html">misc (R)</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/misc" />
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</li>
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<li>
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<a href="techtonique_api_py/index.html">Techtonique API (Python)</a> &nbsp; and
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<a href="techtonique_api_r/index.html">Techtonique API (R)</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/forecastingapi" />
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</li>
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<a href="survivalist/index.html">survivalist</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/survivalist" />
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</li>
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<a href="tisthemachinelearner_r/index.html">tisthemachinelearner (R)</a> &nbsp;
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<a href="tisthemachinelearner/index.html">tisthemachinelearner (Python)</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/tisthemachinelearner" />
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</li>
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<li>
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<a href="genbooster/index.html">genbooster</a>
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&nbsp; | Python: <img src="https://static.pepy.tech/badge/genbooster" />
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</li>
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<li>
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<a href="matern32/index.html">matern32</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/matern32" />
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</li>
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<li>
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<a href="bayesianrvfl/index.html">bayesianrvfl</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/bayesianrvfl" />
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</li>
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<li>
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<a href="after/index.html">after</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/after" />
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</li>
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<li>
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<a href="rvfl/index.html">rvfl</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/rvfl" />
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</li>
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<li>
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<a href="mlreserving/index.html">mlreserving</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/mlreserving" />
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</li>
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<li>
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<a href="glmnetforpython/index.html">GLMNet (Python)</a>
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&nbsp; | Python: <img src="https://static.pepy.tech/badge/glmnetforpython" />
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</li>
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<a href="cybooster/index.html">cybooster</a>
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&nbsp; | Python: <img src="https://static.pepy.tech/badge/cybooster" />
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</li>
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<li>
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<a href="ftsatoo/index.html">ftsatoo</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/ftsatoo" />
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</li>
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<a href="stochasticscenarios/index.html">stochasticscenarios</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/stochasticscenarios" />
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</li>
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<li>
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<a href="synthe/index.html">synthe</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/synthe" />
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</li>
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<li>
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<a href="unifiedml/index.html">unifiedml</a>
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&nbsp; | R: <img src="https://r-universe.techtonique.org/badges/unifiedml" />
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</li>
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</ul>
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&#169; <a href="https://thierrymoudiki.github.io">T. Moudiki</a>
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© <a href="https://thierrymoudiki.github.io">T. Moudiki</a>
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