Probabilistic Time Series Forecasting (predictive simulations) in Microsoft Excel using Python, xlwings lite and www.techtonique.net
https://thierrymoudiki.github.io/blog/2025/03/28/python/xlwings-lite-techtonique
@teeeeeeeee.bsky.social
@teeeeeeeee.bsky.socialProbabilistic Time Series Forecasting (predictive simulations) in Microsoft Excel using Python, xlwings lite and www.techtonique.net
https://thierrymoudiki.github.io/blog/2025/03/28/python/xlwings-lite-techtonique
@teeeeeeeee.bsky.socialProbabilistic Machine Learning (for longitudinal data) Reserving (work in progress)
https://thierrymoudiki.github.io/blog/2025/06/04/python/ml-reserve
@teeeeeeeee.bsky.socialModel calibration with `crossval`
https://thierrymoudiki.github.io/blog/2019/10/04/r/crossval-1
@teeeeeeeee.bsky.socialTime series cross-validation using `crossvalidation` (Part 2)
https://thierrymoudiki.github.io/blog/2021/11/07/r/misc/timeseries/crossvalidation-eval-ts
@teeeeeeeee.bsky.socialR package development workflow (assuming you're using macOS or Linux)
https://thierrymoudiki.github.io/blog/2024/08/27/r/makefile-r-pkg
@teeeeeeeee.bsky.socialnnetsauce version 0.5.0, randomized neural networks on GPU
https://thierrymoudiki.github.io/blog/2020/07/17/python/r/quasirandomizednn/nnetsauce-new-version
@teeeeeeeee.bsky.socialDiffusion models in ESGtoolkit + announcements
https://thierrymoudiki.github.io/blog/2023/10/02/r/esgtoolkit-v062
@teeeeeeeee.bsky.socialPython version of Semi-parametric option pricing based on underlying's historical data (accepted at the osQF 2026 (ex R/Finance) conference)
https://thierrymoudiki.github.io/blog/2026/09/21/python/empirical-pricing
@teeeeeeeee.bsky.socialExplainable 'AI' using Gradient Boosted randomized networks Pt2 (the Lasso)
https://thierrymoudiki.github.io/blog/2020/07/31/python/r/lsboost/explainableml/mlsauce/xai-boosting-2
@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.social
@teeeeeeeee.bsky.socialUnderstanding Boosted Configuration Networks (combined neural networks and boosting): An Intuitive Guide Through Their Hyperparameters
https://thierrymoudiki.github.io/blog/2026/02/16/r/python/bcn-explained
@teeeeeeeee.bsky.socialA web application for forecasting in Python, R, Ruby, C#, JavaScript, PHP, Go, Rust, Java, MATLAB, etc.
https://thierrymoudiki.github.io/blog/2022/11/02/python/r/forecasting/misc/forecasting-api
@teeeeeeeee.bsky.socialProbability of receiving a loan; using learningmachine
https://thierrymoudiki.github.io/blog/2024/05/12/python/r/learningmachine-credit
@teeeeeeeee.bsky.social10 uncertainty quantification methods in nnetsauce forecasting
https://thierrymoudiki.github.io/blog/2024/07/01/python/quasirandomizednn/forecasting/nnetsauce-mts-new
@teeeeeeeee.bsky.socialnnetsauce's introduction as of 2024-02-11 (new version 0.17.0)
https://thierrymoudiki.github.io/blog/2024/02/11/python/quasirandomizednn/nnetsauce-tuto
@teeeeeeeee.bsky.social
@teeeeeeeee.bsky.socialPython version of Semi-parametric option pricing based on underlying's historical data (accepted at the osQF 2026 (ex R/Finance) conference)
https://thierrymoudiki.github.io/blog/2026/09/21/python/empirical-pricing
@teeeeeeeee.bsky.socialForecasting lung disease progression
https://thierrymoudiki.github.io/blog/2020/10/02/misc/r/osic-kaggle
@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
