T. @ Techtonique
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tech, stats, machine learning, computer simulation, numerical optimization https://www.techtonique.net/
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Auto XGBoost, Auto LightGBM, Auto CatBoost, Auto GradientBoosting

https://thierrymoudiki.github.io/blog/2024/08/05/python/r/unibooster

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A lightweight interface to scikit-learn in R Pt.2: probabilistic time series forecasting in conjunction with ahead::dynrmf

https://thierrymoudiki.github.io/blog/2025/04/20/r/tisthemachinelearner-time-series

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Time series cross-validation using crossval

https://thierrymoudiki.github.io/blog/2020/03/27/r/misc/crossval-2

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external regressors in ahead::dynrmf's interface for Machine learning forecasting

https://thierrymoudiki.github.io/blog/2025/09/01/r/external-regressors-in-dynrmf

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Recognizing handwritten digits with Ridge2Classifier

https://thierrymoudiki.github.io/blog/2024/06/03/python/quasirandomizednn/ridge2classifier-loglik

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Generating Synthetic Data with R-vine Copulas using esgtoolkit in R

https://thierrymoudiki.github.io/blog/2025/09/21/r/synthetic-copulas

#Techtonique #DataScience #Python #rstats #MachineLearning
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New activation functions in mlsauce's LSBoost

https://thierrymoudiki.github.io/blog/2021/02/12/r/lsboost/explainableml/mlsauce/activation-functions-lsboost

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Custom errors for cross-validation using crossval::crossval_ml

https://thierrymoudiki.github.io/blog/2020/05/08/r/misc/crossval-custom-errors

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10 uncertainty quantification methods in nnetsauce forecasting

https://thierrymoudiki.github.io/blog/2024/07/01/python/quasirandomizednn/forecasting/nnetsauce-mts-new

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Benchmarking 30 statistical/Machine Learning models on the VN1 Forecasting -- Accuracy challenge

https://thierrymoudiki.github.io/blog/2024/10/04/python/vn1-forecasting-challenge

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Probability of receiving a loan; using learningmachine

https://thierrymoudiki.github.io/blog/2024/05/12/python/r/learningmachine-credit

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Time series cross-validation using `crossvalidation` (Part 2)

https://thierrymoudiki.github.io/blog/2021/11/07/r/misc/timeseries/crossvalidation-eval-ts

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Programming language-agnostic reserving using RidgeCV, LightGBM, XGBoost, and ExtraTrees Machine Learning models

https://thierrymoudiki.github.io/blog/2025/06/13/r/techtonique/mlreserving

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Gradient-Boosting anything (alert: high performance): Part4, Time series forecasting

https://thierrymoudiki.github.io/blog/2024/11/10/python/r/quasirandomizednn/genboosting-mts

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Generating Synthetic Data with R-vine Copulas using esgtoolkit in R

https://thierrymoudiki.github.io/blog/2025/09/21/r/synthetic-copulas

#Techtonique #DataScience #Python #rstats #MachineLearning
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Git/Github for contributing to package development

https://thierrymoudiki.github.io/blog/2020/02/14/misc/git-github

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A classifier that's very accurate (and deep) Pt.2: there are > 90 classifiers in nnetsauce

https://thierrymoudiki.github.io/blog/2024/01/08/python/r/quasirandomizednn/nnetsauce-lazy-classifier-deep-classifier

#Techtonique #DataScience #Python #rstats #MachineLearning
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Time series cross-validation using `crossvalidation` (Part 2)

https://thierrymoudiki.github.io/blog/2021/11/07/r/misc/timeseries/crossvalidation-eval-ts

#Techtonique #DataScience #Python #rstats #MachineLearning
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Generating Synthetic Data with R-vine Copulas using esgtoolkit in R

https://thierrymoudiki.github.io/blog/2025/09/21/r/synthetic-copulas

#Techtonique #DataScience #Python #rstats #MachineLearning
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A new version of nnetsauce (randomized and quasi-randomized 'neural' networks)

https://thierrymoudiki.github.io/blog/2023/04/02/python/r/quasirandomizednn/nnetsauce-python-only

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'Bayesian' optimization of hyperparameters in a R machine learning model using the bayesianrvfl package

https://thierrymoudiki.github.io/blog/2025/04/25/r/bayesian-opt

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Comments section and other news

https://thierrymoudiki.github.io/blog/2020/06/12/misc/comments-section

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Forecasting Monthly Airline Passenger Numbers with Quasi-Randomized Neural Networks

https://thierrymoudiki.github.io/blog/2024/06/17/python/quasirandomizednn/forecasting/nnetsauce-airpassengers

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2020 recap, Gradient Boosting, Generalized Linear Models, AdaOpt with nnetsauce and mlsauce

https://thierrymoudiki.github.io/blog/2020/12/29/python/r/misc/recap-2020-highlights

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