Given that the machine learning models are also a kind of conventional software application, the quality assurance principles applied to…
This post intends to propose a technique termed as Dual Coding for testing or performing quality control checks on machine…
Data science/Machine learning career has primarily been associated with building models which could do numerical or class-related predictions. This is…
In this post, you will learn about the definition of quality of AI / machine learning (ML) models. Getting a good understanding of what is…
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…
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…
In this post, you will learn about different types of test cases which you could come up for testing features of the data…
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…
In this post, I intend to present a perspective on the need for QA / testing team to test the…
This is the first post in the series of posts related to Quality Assurance & Testing Practices and Data Science /…
In this post, you will take the objective test (interview questions and answers) to check your knowledge of Selenium. This…
This article represents some of the key reasons on why one should consider using dockers for testing their applications. Some of the points in…