This paper shares my takeaways, best practices and mitigation steps to mitigate unfairness and bias while designing machine learning algorithms.
Data science projects go wrong either due to flawed models or insufficiently/ incorrectly trained algorithms or emergent bias on new/ unanticipated contexts. Fairness is a human, not a mathematical decision, grounded in shared ethical beliefs. While machine learning does not make decisions based on feelings and emotions, it does inherit a lot of human biases leading to disparate impact. In this era where consequential decisions are algorithm-based it is imperative that they are fair, not perpetuated without users knowledge. …
This paper utilizes Fargo Health Group dataset to forecast the demand for heart examinations expected in 2014 for Abbeville Health Center. It outlines how a business problem can be solved using a data-driven decision making approach and explains the methodology, model leveraged, ethical implications and recommendations for Fargo Health Group.
Fargo Health Group faces the following business problems:
Diamond pricing involves a complex mechanism influenced by multiple factors such as carat, cut, color and price. This article analyzes the correlation between these factors and depicts with visualizations.
Exploratory data analysis
R diamond.csv dataset includes approximately 54K observations with 10 variables including carat, cut, color, clarity, depth, table, price, x (length in mm), y (width in mm) and z (depth in mm). Overall a clean dataset with no missing values or messy data.
Structure of the dataset (R lang)
If you are look to mature your overall StratEx methodology or some aspects of here, the visual below helps lay out the steps for adapting Kaplan-Norton balanced scorecard strategy framework.
Strategy Frameworks — An overview of planning by horizons and balanced scorecard framework
The most beautiful strategy document may be aimless unless it is supported by a solid execution framework. As much as strategy formulation is about picking the right things to focus on it is as much of what not to focus on. Many organizations fail to link strategy to operational plans while some struggle cascading it to all levels of management down to individual contributors.
I am sharing two strategy formulation and execution framework that I have experience setting from ground up for large Fortune 500 companies. I hope the visuals help you in getting a high level idea about these frameworks.
Agile leadership demands that executives create a carefully balanced system that delivers both stability and agility — a system that runs business efficiently and changes the business effectively, and merges the two activities without destroying the system. Agile enables top executives to focus on strategy rather than operational details that are best made by operating managers. Executives come to understand that an hour spent reviewing or second-guessing the work of experienced operating managers creates far less incremental value than an hour invested in developing major cross-functional innovations. Key agile leadership traits include :
Data subset (acs_ny.csv) of the 2010 American Community Survey (ACS) for New York state has been used to create a logistic regression model in R. The purpose of this model is to predict whether a household has an income greater than $150,000.
A couple of models were assessed. The selected model has an accuracy of 83% based on the confusion matrix on the training dataset of 15921 (70% of the records in the total dataset). Precision looks for accuracy of the positive prediction, 30% for the model. …
Exec Director StratEx - I bring to the table blend of data science, finance and strategy management skills with 20+ years of experience in insurance & fintech.