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Currently available:
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<ul>
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<li><ahref="nnetsauce/index.html">nnetsauce for Python</a> |<ahref="nnetsauce_r/">nnetsauce for R</a> Statistical/Machine Learning using Randomized and Quasi-Randomized (neural) networks | <ahref="https://pepy.tech/project/nnetsauce"><imgalt="Downloads" src="https://static.pepy.tech/badge/nnetsauce" /></a><ahref="https://anaconda.org/conda-forge/nnetsauce"><imgsrc="https://anaconda.org/conda-forge/nnetsauce/badges/downloads.svg" /></a></li>
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<li><ahref="nnetsauce/index.html">nnetsauce for Python</a> and<ahref="nnetsauce_r/">nnetsauce for R</a> Statistical/Machine Learning using Randomized and Quasi-Randomized (neural) networks and <ahref="https://pepy.tech/project/nnetsauce"><imgalt="Downloads" src="https://static.pepy.tech/badge/nnetsauce" /></a><ahref="https://anaconda.org/conda-forge/nnetsauce"><imgsrc="https://anaconda.org/conda-forge/nnetsauce/badges/downloads.svg" /></a></li>
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<li><ahref="mlsauce/index.html">mlsauce for Python</a> and <ahref="mlsauce_r/index.html">mlsauce for R</a> Miscellaneous Statistical/Machine Learning stuff | <ahref="https://pepy.tech/project/mlsauce"><imgalt="Downloads" src="https://static.pepy.tech/badge/mlsauce" /></a><ahref="https://anaconda.org/conda-forge/mlsauce"><imgsrc="https://anaconda.org/conda-forge/mlsauce/badges/downloads.svg" /></a></li>
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<li><ahref="ahead/index.html">ahead (for R)</a> and <ahref="ahead_python/index.html">ahead (for Python)</a> Univariate and Multivariate time series forecasting | <ahref="https://pepy.tech/project/ahead"><imgalt="Downloads" src="https://static.pepy.tech/badge/ahead" /></a><ahref="https://anaconda.org/conda-forge/ahead_python"><imgsrc="https://anaconda.org/conda-forge/ahead_python/badges/downloads.svg" /></a></li>
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<li><ahref="GPopt/index.html">gpopt</a> Bayesian optimization using Gaussian Process Regression | <ahref="https://pepy.tech/project/gpopt"><imgalt="Downloads" src="https://static.pepy.tech/badge/gpopt" /></a></li>
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