Graham Harrison – Medium

Graham Harrison

Published in
Towards Data Science

A Proposed Perfect Package Prototype for Python Projects

How to structure your Python package projects to ensure efficiency, effectiveness and future-proofing

Jun 18

A Proposed Perfect Package Prototype for Python Projects

Jun 18

Published in
Towards Data Science

Causal Validation: A Unified Theory of Everything

How to detect and fix any type of error in a directed acyclic graph so that it is a valid representation of the underlying data

May 16

Causal Validation: A Unified Theory of Everything

May 16

Published in
Towards Data Science

Understanding V-Structures and the Role They Play in Causal Validation and Causal Inference

How to Detect and Correct the Direction of Causal Links in a Directed Acyclic Graph that are Incorrect When Compared to the Underlying Data

Mar 19

Understanding V-Structures and the Role They Play in Causal Validation and Causal Inference

Mar 19

Published in
Towards Data Science

Understanding Junctions (Chains, Forks and Colliders) and the Role they Play in Causal Inference

Explaining junctions using correlation, independence and regression to understand their critical importance in causal inference

Jan 31

Understanding Junctions (Chains, Forks and Colliders) and the Role they Play in Causal Inference

Jan 31

Published in
Towards Data Science

Understanding Independence and Why it is Critical in Causal Inference and Causal Validation

A step-by-step guide in understanding independence and how to apply it to validate directed acyclic graphs in causal validation using…

Dec 7, 2023

Understanding Independence and Why it is Critical in Causal Inference and Causal Validation

Dec 7, 2023

Published in
Towards Data Science

Demystifying Dependence and Why it is Important in Causal Inference and Causal Validation

A step-by-step guide in understanding the concept of dependence and how to apply it to validate directed acyclic graphs in causal inference

Nov 11, 2023

Demystifying Dependence and Why it is Important in Causal Inference and Causal Validation

Nov 11, 2023

Published in
Towards Data Science

How to Extend Pandas DataFrames with Custom Methods to Supercharge Code Functionality & Readability

A step-by-step guide to extending pandas DataFrames with custom methods including full examples for implementing probability and expectancy

Oct 10, 2023

How to Extend Pandas DataFrames with Custom Methods to Supercharge Code Functionality & Readability

Oct 10, 2023

Published in
Towards Data Science

Unlock the Secrets of Causal Inference with a Master Class in Directed Acyclic Graphs

A step-by-step explanation of Directed Acyclic Graphs from the basics through to more advanced aspects

Apr 6, 2023

Unlock the Secrets of Causal Inference with a Master Class in Directed Acyclic Graphs

Apr 6, 2023

Published in
Towards Data Science

Unlock the Power of Causal Inference & Front-door Adjustment: An In-depth Guide for Data Scientists

A full explanation of causal inference front-door adjustment with examples including all the Python source code

Feb 14, 2023

Unlock the Power of Causal Inference & Front-door Adjustment: An In-depth Guide for Data Scientists

Feb 14, 2023

Published in
Towards Data Science

How to Calculate Conditional Probabilities from Any DataFrame in 3 Lines of Code

Learn to write a simple Python function that will calculate conditional probabilities using notation like p(exam=1 | study=1)

Feb 10, 2023

How to Calculate Conditional Probabilities from Any DataFrame in 3 Lines of Code

Feb 10, 2023

Graham Harrison

Graham Harrison

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