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Effect Estimation with PyMC: Adstock, Saturation & Diminishing Returns", "url": "https://juanitorduz.github.io/pymc_mmm/", "published_at": "2022-02-11T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256eb32bfe5", "title": "Media Effect Estimation with Orbit's KTR Model", "url": "https://juanitorduz.github.io/orbit_mmm/", "published_at": "2022-02-04T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256ebd8d7fb", "title": "Unobserved Components Model as a Bayesian Model with PyMC", "url": "https://juanitorduz.github.io/uc_pymc/", "published_at": "2021-12-10T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256ec8d2ab9", "title": "ISLR2 - Survival Analysis Lab (lifelines)", "url": "https://juanitorduz.github.io/islr2_survival_analysis/", "published_at": "2021-09-01T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256ed57ef64", "title": "Exploring Tools for Interpretable Machine Learning", "url": "https://juanitorduz.github.io/interpretable_ml/", "published_at": "2021-07-01T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256ed8e3268", "title": "Feature Engineering: patsy as FormulaTransformer", "url": "https://juanitorduz.github.io/formula_transformer/", "published_at": "2021-05-01T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256ee6329be", "title": "GLM in PyMC3: Out-Of-Sample Predictions", "url": "https://juanitorduz.github.io/glm_pymc3/", "published_at": "2021-01-04T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256ef2bdcd2", "title": "Gaussian Processes for Time Series Forecasting with PyMC3", "url": "https://juanitorduz.github.io/gp_ts_pymc3/", "published_at": "2021-01-02T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256ef48de42", "title": "Simple Bayesian Linear Regression with TensorFlow Probability", "url": "https://juanitorduz.github.io/tfp_lm/", "published_at": "2020-10-06T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256eff233ed", "title": "Open Data: Berlin Kitas", "url": "https://juanitorduz.github.io/kitas_berlin/", "published_at": "2020-09-19T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f0dd961d", "title": "A Simple Hamiltonian Monte Carlo Example with TensorFlow Probability", "url": "https://juanitorduz.github.io/tfp_hcm/", "published_at": "2020-07-24T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f1240d18", "title": "Regression Analysis & Visualization", "url": "https://juanitorduz.github.io/lm_viz/", "published_at": "2020-06-26T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f180db0d", "title": "A Glimpse into TensorFlow Probability Distributions", "url": "https://juanitorduz.github.io/intro_tfd/", "published_at": "2020-06-16T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f1d02e64", "title": "Disease Spread Simulation (Animation)", "url": "https://juanitorduz.github.io/infection_sim/", "published_at": "2020-04-28T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f1ec7b6e", "title": "Getting Started with Spectral Clustering", "url": "https://juanitorduz.github.io/spectral_clustering/", "published_at": "2020-04-04T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f2d471c7", "title": "The Volume of the d-Ball via Monte Carlo Simulation", "url": "https://juanitorduz.github.io/vol_d_ball/", "published_at": "2020-02-24T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f3947123", "title": "Forecasting Weekly Data with Prophet", "url": "https://juanitorduz.github.io/fb_prophet/", "published_at": "2020-02-21T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f46289ee", "title": "Exploring TensorFlow Probability STS Forecasting", "url": "https://juanitorduz.github.io/intro_sts_tfp/", "published_at": "2020-02-11T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f48dc709", "title": "Intro ML in Production: Flask, Docker and GitHub Actions", "url": "https://juanitorduz.github.io/ml_prod_intro/", "published_at": "2020-01-28T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f53475db", "title": "Drawing Manifolds in LaTeX with TikZ", "url": "https://juanitorduz.github.io/manifold_fig_latex/", "published_at": "2020-01-10T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f60dbb70", "title": "Open Data: Germany Maps Viz", "url": "https://juanitorduz.github.io/germany_plots/", "published_at": "2020-01-07T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f6f45589", "title": "The Graph Laplacian & Semi-Supervised Clustering", "url": "https://juanitorduz.github.io/semi_supervised_clustering/", "published_at": "2019-12-05T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f7e55ad0", "title": "The Lapacian on the 2-Torus", "url": "https://juanitorduz.github.io/laplacian_2torus/", "published_at": "2019-10-13T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f870a098", "title": "PyData Berlin 2019: Gaussian Processes for Time Series Forecasting (scikit-learn)", "url": "https://juanitorduz.github.io/gaussian_process_time_series/", "published_at": "2019-10-10T00:00:00+00:00" }, { "id": "01a08792-1001-71c3-b85c-8256f963af57", "title": "satRday Berlin 2019: Remedies for Severe Class Imbalance", "url": "https://juanitorduz.github.io/class_imbalance/", "published_at": "2019-06-15T00:00:00+00:00" } ] posts Claim your blog

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2026

Multilevel Regression and Poststratification (MRP) in PyMC original ↗

6 Sept 2026

Structural Causal Models with PathMC original ↗

29 Aug 2026

Forecasting Retail Demand Under Stockouts original ↗

12 Jul 2026

Ads, ROAS and Budgets: Interpreting and Communicating Statistical Models original ↗

27 May 2026

Exponential Smoothing with NumPyro: State Space Form original ↗

19 Apr 2026

The Frugal Parameterization for Bayesian Causal Inference in PyMC original ↗

11 Apr 2026

Mediation Analysis and (In)Direct Effects with PyMC original ↗

17 Mar 2026

Intuition behind CRPS original ↗

11 Mar 2026

Bayesian Power Analysis for A/B Testing original ↗

5 Mar 2026

In-Sample \(R^2\) is Not a Good Metric for Decision Making original ↗

22 Feb 2026

Fixed and Random Effects Models: A Simulated Study original ↗

3 Feb 2026

A Bayesian Decision Theory Workflow: Port to NumPyro original ↗

25 Jan 2026

Forecasting Hierarchical Models - Part III original ↗

5 Jan 2026

Machine Learning for Optimization: Toy Example original ↗

1 Jan 2026

2025

CATE Estimation with Causal Effect Variational Autoencoders original ↗

13 Dec 2025

Causal Effect Estimation with Variational Inference and Latent Confounders original ↗

10 Dec 2025

Causal Inference with Multilevel Models: The Electric Company Example original ↗

28 Nov 2025

Introduction to Causal Inference with PPLs original ↗

27 Nov 2025

Bayesian Vector Autoregressive Models in NumPyro original ↗

3 Oct 2025

PyData Berlin 2025: Introduction to Stochastic Variational Inference with NumPyro original ↗

1 Sept 2025

Hierarchical Revenue & Retention Modeling original ↗

4 Aug 2025

Vectorize ROC Curve for Bayesian Models original ↗

30 Jun 2025

Introduction to Bayesian Power Analysis: Exclude a Null Value original ↗

29 Apr 2025

Prior Predictive Modeling in Bayesian AB Testing original ↗

11 Mar 2025

Notes on Hierarchical Hilbert Space Gaussian Processes original ↗

1 Jan 2025

2024

Hacking the TSB Model for Intermittent Time Series to Accommodate for Availability Constraints original ↗

25 Nov 2024

Bayesian CUPED & Sensitivity Analysis original ↗

29 Oct 2024

Electricity Demand Forecast: Dynamic Time-Series Model with Prior Calibration original ↗

7 Oct 2024

Electricity Demand Forecast: Dynamic Time-Series Model original ↗

6 Oct 2024

From Pyro to NumPyro: Forecasting Hierarchical Models - Part II original ↗

5 Oct 2024

From Pyro to NumPyro: Forecasting Hierarchical Models - Part I original ↗

3 Oct 2024

From Pyro to NumPyro: Forecasting a univariate, heavy tailed time series original ↗

1 Oct 2024

Hierarchical Pricing Elasticity Models original ↗

1 Aug 2024

Multilevel Elasticities for a Single SKU - Part III.original ↗

19 Jul 2024

Hierarchical Exponential Smoothing Model original ↗

7 Jun 2024

Demand Forecasting with Censored Likelihood original ↗

21 Apr 2024

A Conceptual and Practical Introduction to Hilbert Space GPs Approximation Methods original ↗

18 Apr 2024

Bayesian Censoring Data Modeling original ↗

26 Feb 2024

Zero-Inflated TSB Model original ↗

20 Feb 2024

TSB Method for Intermittent Time Series Forecasting in NumPyro original ↗

17 Feb 2024

Croston's Method for Intermittent Time Series Forecasting in NumPyro original ↗

15 Feb 2024

Notes on an ARMA(1, 1) Model with NumPyro original ↗

13 Feb 2024

Notes on Exponential Smoothing with NumPyro original ↗

11 Feb 2024

Media Mix Model and Experimental Calibration: A Simulation Study original ↗

4 Feb 2024

Cohort Revenue Retention Analysis with Flax and NumPyro original ↗

8 Jan 2024

Flax and NumPyro Toy Example original ↗

5 Jan 2024

Time Series Modeling with HSGP: Baby Births Example original ↗

2 Jan 2024

2023

Non-Parametric Product Life Cycle Modeling original ↗

10 Dec 2023

NumPyro with Pathfinder original ↗

4 Dec 2023

Causal Bandits: Causality, Marketing & Simulations original ↗

19 Nov 2023

Multilevel Elasticities for a Single SKU - Part II.original ↗

13 Nov 2023

Multilevel Elasticities for a Single SKU - Part I.original ↗

10 Aug 2023

Time-Varying Regression Coefficients via Hilbert Space Gaussian Process Approximation original ↗

5 Jul 2023

Using Data Science for Bad Decision-Making: A Case Study original ↗

16 Jun 2023

Regression Discontinuity with GLMs and Kernel Weighting original ↗

10 Jun 2023

ATE Estimation for Count Data original ↗

7 Jun 2023

ATE Estimation with Logistic Regression original ↗

4 Jun 2023

Bayesian Methods in Modern Marketing Analytics Webinar with PyMC Labs original ↗

31 May 2023

How to vectorize an scikit-learn transformer over a numpy array?original ↗

1 May 2023

Counting the Number of Kitas per PLZ in Berlin using a Hierarchical Bayesian Model original ↗

28 Apr 2023

Simple Hierarchical Model with NumPyro: Cookie Chips Example original ↗

24 Apr 2023

Experimentation, Non-Compliance and Instrumental Variables with PyMC original ↗

20 Feb 2023

Cohort Revenue & Retention Analysis: A Bayesian Approach original ↗

23 Jan 2023

Cohort Retention Analysis with BART original ↗

2 Jan 2023

2022

A Simple Cohort Retention Analysis in PyMC original ↗

20 Dec 2022

Geo-Experimentation via Time Based Regression in PyMC original ↗

1 Dec 2022

Offline Campaign Analysis Measurement: A journey through causal impact, geo-experimentation and synthetic control original ↗

25 Oct 2022

Scikit-Learn Example in PyMC: Gaussian Process Classifier original ↗

24 Sept 2022

Synthetic Control in PyMC original ↗

9 Aug 2022

Modeling Short Time Series with Prior Knowledge in PyMC original ↗

19 Jul 2022

Time-Varying Regression Coefficients via Gaussian Random Walk in PyMC original ↗

3 Jul 2022

Data Talks Club: Machine Learning in Marketing original ↗

17 May 2022

PyConDE & PyData Berlin 2022: Introduction to Uplift Modeling original ↗

11 Apr 2022

Gamma-Gamma Model of Monetary Value in PyMC original ↗

29 Mar 2022

BG/NBD Model in PyMC original ↗

3 Mar 2022

Media Effect Estimation with PyMC: Adstock, Saturation & Diminishing Returns original ↗

11 Feb 2022

Media Effect Estimation with Orbit's KTR Model original ↗

4 Feb 2022

2021

Unobserved Components Model as a Bayesian Model with PyMC original ↗

10 Dec 2021

ISLR2 - Survival Analysis Lab (lifelines)original ↗

1 Sept 2021

Exploring Tools for Interpretable Machine Learning original ↗

1 Jul 2021

Feature Engineering: patsy as FormulaTransformer original ↗

1 May 2021

GLM in PyMC3: Out-Of-Sample Predictions original ↗

4 Jan 2021

Gaussian Processes for Time Series Forecasting with PyMC3 original ↗

2 Jan 2021

2020

Simple Bayesian Linear Regression with TensorFlow Probability original ↗

6 Oct 2020

Open Data: Berlin Kitas original ↗

19 Sept 2020

A Simple Hamiltonian Monte Carlo Example with TensorFlow Probability original ↗

24 Jul 2020

Regression Analysis & Visualization original ↗

26 Jun 2020

A Glimpse into TensorFlow Probability Distributions original ↗

16 Jun 2020

Disease Spread Simulation (Animation)original ↗

28 Apr 2020

Getting Started with Spectral Clustering original ↗

4 Apr 2020

The Volume of the d-Ball via Monte Carlo Simulation original ↗

24 Feb 2020

Forecasting Weekly Data with Prophet original ↗

21 Feb 2020

Exploring TensorFlow Probability STS Forecasting original ↗

11 Feb 2020

Intro ML in Production: Flask, Docker and GitHub Actions original ↗

28 Jan 2020

Drawing Manifolds in LaTeX with TikZ original ↗

10 Jan 2020

Open Data: Germany Maps Viz original ↗

7 Jan 2020

2019

The Graph Laplacian & Semi-Supervised Clustering original ↗

5 Dec 2019

The Lapacian on the 2-Torus original ↗

13 Oct 2019

PyData Berlin 2019: Gaussian Processes for Time Series Forecasting (scikit-learn)original ↗

10 Oct 2019

satRday Berlin 2019: Remedies for Severe Class Imbalance original ↗

15 Jun 2019