@juniorjumbong.bsky.social
Reposted
In this new technical guide, @juniorjumbong.bsky.social demonstrates how to properly implement the Fourier transform for continuous functions in Python.
Implementing the Fourier Transform Numerically in Python: A Step-by-Step Guide | Towards Data Science
What if the FFT functions in NumPy and SciPy don’t actually compute the Fourier transform you think they do?
towardsdatascience.com
October 21, 2025 at 6:18 PM
In this new technical guide, @juniorjumbong.bsky.social demonstrates how to properly implement the Fourier transform for continuous functions in Python.
Reposted
Discover why the popular MissForest algorithm fails in predictive modeling and can introduce data leakage. @juniorjumbong.bsky.social's new article explains its critical limitation and introduces MissForestPredict as the solution for unbiased model evaluation.
Why MissForest Fails in Prediction Tasks: A Key Limitation You Need to Keep in Mind | Towards Data Science
Why the original MissForest algorithm cannot be directly applied for predictive modeling, and how MissForestPredict solves this problem
towardsdatascience.com
September 27, 2025 at 1:47 PM
Discover why the popular MissForest algorithm fails in predictive modeling and can introduce data leakage. @juniorjumbong.bsky.social's new article explains its critical limitation and introduces MissForestPredict as the solution for unbiased model evaluation.
Thrilled to have my article featured by @towardsdatascience.com 🙏
Why MissForest (2012) fails in predictive modeling and how MissForestPredict (2024) solves this limitation.
Read here 👉
towardsdatascience.com/why-missfore...
Why MissForest (2012) fails in predictive modeling and how MissForestPredict (2024) solves this limitation.
Read here 👉
towardsdatascience.com/why-missfore...
Why MissForest Fails in Prediction Tasks: A Key Limitation You Need to Keep in Mind | Towards Data Science
Why the original MissForest algorithm cannot be directly applied for predictive modeling, and how MissForestPredict solves this problem
towardsdatascience.com
September 26, 2025 at 6:11 PM
Thrilled to have my article featured by @towardsdatascience.com 🙏
Why MissForest (2012) fails in predictive modeling and how MissForestPredict (2024) solves this limitation.
Read here 👉
towardsdatascience.com/why-missfore...
Why MissForest (2012) fails in predictive modeling and how MissForestPredict (2024) solves this limitation.
Read here 👉
towardsdatascience.com/why-missfore...
⚽ A new era in the Premier League?
PSI & Cramér’s V reveal subtle but real changes in goal patterns between 2023/24 & 2024/25.
See the stats + visualizations:https://medium.com/python-in-plain-english/have-premier-league-goal-distributions-changed-between-2023-24-and-2024-25-7b9e0614f090
PSI & Cramér’s V reveal subtle but real changes in goal patterns between 2023/24 & 2024/25.
See the stats + visualizations:https://medium.com/python-in-plain-english/have-premier-league-goal-distributions-changed-between-2023-24-and-2024-25-7b9e0614f090
Population Stability Index and Cramér’s V: Measuring Goal Distribution Shifts in the Premier League.
Comparing Goal Distributions Across Seasons: 2023/24 vs 2024/25 using population stability index and Cramer’s V.
medium.com
September 15, 2025 at 6:50 AM
⚽ A new era in the Premier League?
PSI & Cramér’s V reveal subtle but real changes in goal patterns between 2023/24 & 2024/25.
See the stats + visualizations:https://medium.com/python-in-plain-english/have-premier-league-goal-distributions-changed-between-2023-24-and-2024-25-7b9e0614f090
PSI & Cramér’s V reveal subtle but real changes in goal patterns between 2023/24 & 2024/25.
See the stats + visualizations:https://medium.com/python-in-plain-english/have-premier-league-goal-distributions-changed-between-2023-24-and-2024-25-7b9e0614f090
Just published on Towards Data Science!
Is your training data truly representative?
In this article, I show how to check it with PSI and Cramér’s V in Python to detect population drift.
[Representativeness using PSI](towardsdatascience.com/assessment-o...)
Thanks @towardsdatascience.com
Is your training data truly representative?
In this article, I show how to check it with PSI and Cramér’s V in Python to detect population drift.
[Representativeness using PSI](towardsdatascience.com/assessment-o...)
Thanks @towardsdatascience.com
Is Your Training Data Representative? A Guide to Checking with PSI in Python | Towards Data Science
Comparing Variable Distributions Between Two Datasets Using Population Stability Index (PSI) and Cramér’s V.
towardsdatascience.com
September 11, 2025 at 5:36 PM
Just published on Towards Data Science!
Is your training data truly representative?
In this article, I show how to check it with PSI and Cramér’s V in Python to detect population drift.
[Representativeness using PSI](towardsdatascience.com/assessment-o...)
Thanks @towardsdatascience.com
Is your training data truly representative?
In this article, I show how to check it with PSI and Cramér’s V in Python to detect population drift.
[Representativeness using PSI](towardsdatascience.com/assessment-o...)
Thanks @towardsdatascience.com
Which Variables Belong in Your Regression Model? Here’s How to Decide.
We reduced over 100 variables to just 19, simplifying the model while maintaining accuracy and interpretability.
Read it here: (towardsdatascience.com/model-select...)
Thanks to @towardsdatascience.com for featuring it!
We reduced over 100 variables to just 19, simplifying the model while maintaining accuracy and interpretability.
Read it here: (towardsdatascience.com/model-select...)
Thanks to @towardsdatascience.com for featuring it!
Stepwise Selection Made Simple: Improve Your Regression Models in Python | Towards Data Science
Dimensionality reduction in linear regression: classical stepwise methods and a Python application on real-world data
towardsdatascience.com
August 30, 2025 at 12:54 AM
Which Variables Belong in Your Regression Model? Here’s How to Decide.
We reduced over 100 variables to just 19, simplifying the model while maintaining accuracy and interpretability.
Read it here: (towardsdatascience.com/model-select...)
Thanks to @towardsdatascience.com for featuring it!
We reduced over 100 variables to just 19, simplifying the model while maintaining accuracy and interpretability.
Read it here: (towardsdatascience.com/model-select...)
Thanks to @towardsdatascience.com for featuring it!