Univariate and Multivariate Probabilistic Forecasting with nnetsauce and TabPFN
https://thierrymoudiki.github.io/blog/2025/01/14/python/forecasting-nnetsauce-tabpfn
@teeeeeeeee.bsky.social
@teeeeeeeee.bsky.socialUnivariate and Multivariate Probabilistic Forecasting with nnetsauce and TabPFN
https://thierrymoudiki.github.io/blog/2025/01/14/python/forecasting-nnetsauce-tabpfn
@teeeeeeeee.bsky.socialESGtoolkit, a tool for Monte Carlo simulation (v0.2.0)
https://thierrymoudiki.github.io/blog/2020/01/17/r/esgtoolkit-1
@teeeeeeeee.bsky.socialtisthemachinelearner: New Workflow with uv for R Integration of scikit-learn
https://thierrymoudiki.github.io/blog/2025/12/01/r/python/tisthemlnewworkflow
@teeeeeeeee.bsky.socialmlsauce version 0.8.10: Statistical/Machine Learning with Python and R
https://thierrymoudiki.github.io/blog/2023/11/05/python/r/adaopt/lsboost/mlsauce_classification
@teeeeeeeee.bsky.sociallearningmachine v1.1.2: for Python
https://thierrymoudiki.github.io/blog/2024/04/01/python/learningmachine-python
@teeeeeeeee.bsky.socialStatistical/Machine Learning explainability using Kernel Ridge Regression surrogates
https://thierrymoudiki.github.io/blog/2020/11/06/explainableml/r/misc/xai-krr-surrogate
@teeeeeeeee.bsky.socialUsing R in Python for statistical learning/data science
https://thierrymoudiki.github.io/blog/2019/10/11/python/r/rpy2
@teeeeeeeee.bsky.sociallearningmachine for Python (new version)
https://thierrymoudiki.github.io/blog/2024/07/15/python/learningmachine-python
@teeeeeeeee.bsky.socialCommand Line Interface (CLI) for techtonique.net's API
https://thierrymoudiki.github.io/blog/2025/01/31/python/r/techtonique/techtonique-CLI
@teeeeeeeee.bsky.social
@teeeeeeeee.bsky.socialtisthemachinelearner: New Workflow with uv for R Integration of scikit-learn
https://thierrymoudiki.github.io/blog/2025/12/01/r/python/tisthemlnewworkflow
@teeeeeeeee.bsky.socialForecasting with XGBoost embedded in Quasi-Randomized Neural Networks
https://thierrymoudiki.github.io/blog/2024/06/24/python/quasirandomizednn/forecasting/nnetsauce-mts-boost
@teeeeeeeee.bsky.socialGradient-Boosting anything (alert: high performance): Part4, Time series forecasting
https://thierrymoudiki.github.io/blog/2024/11/10/python/r/quasirandomizednn/genboosting-mts
@teeeeeeeee.bsky.socialLinear model, xgboost and randomForest cross-validation using crossval::crossval_ml
https://thierrymoudiki.github.io/blog/2020/04/17/r/misc/crossval-3
@teeeeeeeee.bsky.socialrtopy (v0.1.1): calling R functions in Python
https://thierrymoudiki.github.io/blog/2024/03/04/python/r/rtopyintro
@teeeeeeeee.bsky.social
@teeeeeeeee.bsky.socialSkip the R/Python runtime: fast tabular dashboards with Observable Framework
https://thierrymoudiki.github.io/blog/2026/08/31/python/r/javascript/observable-framework
@teeeeeeeee.bsky.socialClassify penguins with nnetsauce's MultitaskClassifier
https://thierrymoudiki.github.io/blog/2020/12/11/r/quasirandomizednn/classify-penguins-nnetsauce
@teeeeeeeee.bsky.socialVersion 0.4.0 of nnetsauce, with fruits and breast cancer classification
https://thierrymoudiki.github.io/blog/2020/02/28/python/quasirandomizednn/r/nnetsauce-new-version
@teeeeeeeee.bsky.socialYou Don't Need to Learn All the Weights on tabular data: The Case for rvflnet (a nonlinear expressive glmnet) on regression, classification and survival analysis
https://thierrymoudiki.github.io/blog/2026/05/02/r/rvflnet
