QA – How Reliable are your Machine Learning Systems?
In this post, you will learn about different aspects of creating a machine learning system with high reliability. It should…
Configure Nexus Repository for Docker Registry (Windows)
In this post, you will learn about how to configure Nexus Repository OSS on Windows as a Docker Private Registry. The goal of doing this can…
ML Metrics – Sensitivity vs Specificity Difference
In this post, we will try and understand the concepts behind evaluation metrics such as sensitivity and specificity which is used to…
Why is QA needed for Machine Learning Models?
Given that the machine learning models are also a kind of conventional software application, the quality assurance principles applied to…
Testing Machine Learning Models on Dual Coding Principles
This post intends to propose a technique termed as Dual Coding for testing or performing quality control checks on machine…
QA – Blackbox Testing for Machine Learning Models
Data science/Machine learning career has primarily been associated with building models which could do numerical or class-related predictions. This is…
Assessing Quality of AI Models from QA Standpoint
In this post, you will learn about the definition of quality of AI / machine learning (ML) models. Getting a good understanding of what is…
QA – Metamorphic Testing for Machine Learning Models
In this post, you will learn about how metamorphic testing could be used for performing quality control checks/testing on machine learning models. The post is…
QA – Why Machine Learning Systems are Non-testable
This post represents views on why machine learning systems or models are termed as non-testable from quality control/quality assurance perspectives. Before I proceed ahead, let…
QA – Testing Features of Machine Learning Models
In this post, you will learn about different types of test cases which you could come up for testing features of the data…
QA of Machine Learning Models with PDCA Cycle
The primary goal of establishing and implementing Quality Assurance (QA) practices for machine learning/data science projects or, projects using machine learning models is to…
QA & Data Science – How to Test Features Relevance
In this post, I intend to present a perspective on the need for QA / testing team to test the…
Quality Assurance / Testing the Machine Learning Model
This is the first post in the series of posts related to Quality Assurance & Testing Practices and Data Science /…
Data Science – P-Value Explained with Examples
Are you one of the data science/machine learning beginners who wants to learn about P-Value using some examples? Are you…
Is Blockchain a Database?
This video represents a comparison/difference between Blockchain and a traditional database form. Some of the following aspects of Blockchain is…
Blockchain – Opportunities & Risks for Financial Institutions
Here is a good white paper/research report published by European Banking Authority (EBA) detailing out the opportunities and risks associated…