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@@ -69,25 +69,25 @@ <h1>Techtonique</h1>
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<br>
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Currently available:
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<ul>
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<!-- nnetsauce - Corrected R badge URL -->
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/nnetsauce.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/nnetsauce.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/mlsauce.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/mlsauce.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/ahead.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/ahead.svg" />
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<!-- gpopt - Python only, no R badge -->
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<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>
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/bcn.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/bcn.svg" />
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<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>
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/esgtoolkit.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/esgtoolkit.svg" />
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<!-- rtopy - Python only, no R badge -->
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<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>
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<a href="crossvalidation/index.html">crossvalidation</a> &nbsp; Generic R functions for cross-validation <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/crossvalidation.svg" />
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<a href="crossvalidation/index.html">crossvalidation</a> &nbsp; Generic R functions for cross-validation <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/crossvalidation.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/learningmachine.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/learningmachine.svg" />
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<!-- unifiedbooster - Python only, no R badge -->
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<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>
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<a href="misc/index.html">misc</a> &nbsp; Miscellaneous useful R functions <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/misc.svg" />
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<a href="misc/index.html">misc</a> &nbsp; Miscellaneous useful R functions <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/misc.svg" />
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<!-- Techtonique API - Corrected to forecastingapi -->
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/forecastingapi.svg" />
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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/forecastingapi.svg" />
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<!-- survivalist - Python only, no R badge -->
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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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<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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/tisthemachinelearner.svg" />
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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> <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/tisthemachinelearner.svg" />
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<!-- genbooster - Python only, no R badge -->
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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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<a href="matern32/index.html">matern32</a> &nbsp; Interpretable Kernel Ridge Regression using Matern 3/2 kernels in R. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/matern32.svg" />
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<a href="matern32/index.html">matern32</a> &nbsp; Interpretable Kernel Ridge Regression using Matern 3/2 kernels in R. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/matern32.svg" />
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<a href="bayesianrvfl/index.html">bayesianrvfl</a> &nbsp; Adaptive Bayesian (NON)Linear regression in R. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/bayesianrvfl.svg" />
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<a href="bayesianrvfl/index.html">bayesianrvfl</a> &nbsp; Adaptive Bayesian (NON)Linear regression in R. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/bayesianrvfl.svg" />
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<!-- after - R only, added badge (assuming package exists in your system) -->
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<!-- after - Updated to grand-total -->
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<a href="after/index.html">after</a> &nbsp; Univariate and multivariate time series forecasting with multiple models. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/after.svg" />
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<a href="after/index.html">after</a> &nbsp; Univariate and multivariate time series forecasting with multiple models. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/after.svg" />
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<a href="rvfl/index.html">rvfl</a> &nbsp; Random Vector Functional Link (RVFL) networks in R. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/rvfl.svg" />
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<a href="rvfl/index.html">rvfl</a> &nbsp; Random Vector Functional Link (RVFL) networks in R. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/rvfl.svg" />
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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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<a href="ftsatoo/index.html">ftsatoo</a> &nbsp; Functions for visualizing, modeling, (generic) forecasting and hypothesis testing of functional time series. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/ftsatoo.svg" />
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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. <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/ftsatoo.svg" />
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<a href="stochasticscenarios/index.html">stochasticscenarios</a> A Package for Asset Projection Using Stochastic Simulation <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/stochasticscenarios.svg" />
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<a href="stochasticscenarios/index.html">stochasticscenarios</a> A Package for Asset Projection Using Stochastic Simulation <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/stochasticscenarios.svg" />
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<!-- synthe - Python only, no R badge -->
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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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<!-- unifiedml - R only, added badge (assuming package exists in your system) -->
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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) <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/last-month/unifiedml.svg" />
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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) <img alt="R Downloads" src="https://r-packages.techtonique.net/badges/downloads/grand-total/unifiedml.svg" />
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