Tutorial on Accumulated Local Effects (ALE), focused on its use, interpretation, and pros & cons

Review of Previous Posts

Explainable Machine Learning (XAI) refers to efforts to make sure that artificial intelligence programs are transparent in their purposes and how they work. [1] This is the third post among the XAI series that I plan to write.

In my first post, I introduced the concept of Partial Dependence (PD)…

Tutorial on Individual Conditional Expectation (ICE) Curves, its advantages and disadvantages, how it is different from PDP and how to make use and interpret it

Review of Previous Post

Explainable Machine Learning (XAI) refers to efforts to make sure that artificial intelligence programs are transparent in their purposes and how they work. [1] This is the second post among the XAI series that I plan to write.

In my previous post, I introduced the concept of Partial Dependence (PD)…

Primer on Partial Dependence Plot, its advantages and disadvantages, how to make use and interpret it

Explainable Machine Learning (XAI)

Explainable Machine Learning (XAI) refers to efforts to make sure that artificial intelligence programs are transparent in their purposes and how they work. [1] It has been one of the hottest keywords in the Data Science and Artificial Intelligence community in the recent few years. This is understandable because a…

Methods to keep track of changes (drift) in data after model deployment

What is Model Drift?

You are done with making a fantastic model that performs very well even on various validation sets. You are ready to deploy the model for real-word data. After deployment, however, you discover that the performance of the model is very poor. What happened? What could have gone wrong?

Model deployment…

Counterfactual explanation is a powerful but straightforward method to improve explanability of machine learning models

Intro

The biggest shortcoming of many machine learning models and neural networks is their “blackbox” nature. Which feature was most influential in this predicted output that we got for an instance? …

Vaex is a rising Big Data Lib for Python and we explore its strengths and limitations and some starting code to use it

General Description of Vaex

As of now, there are various big data libraries available for Python. Dask and Pyspark are well-known examples and H2O is relatively more nascent. …

Python has become the go-to language in the field of Data Science. However, other programming languages or statistical software are still being actively used depending on the particular industry or field you are immersed in. One best example is the field of Economics Research. Many economists and post-doctoral employees use…

Seungjun (Josh) Kim

Data Scientist; Artist (Singing, Percussion)

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