AB Testing&Canary Deployments - Learn Data Science with Travis

AB-Testing-and-Canary-Deployments

AB testing and Canary deployments are two essential methodologies in the realm of software development and product optimization. AB testing is a statistical approach that compares two or more variations of a product to determine which one performs better in achieving specific goals, such as user engagement or conversion rates. On the other hand, Canary deployments involve releasing a new version of software to a small subset of users before a full rollout. This allows teams to monitor performance and gather feedback, minimizing risks associated with new releases. Together, these techniques enable data-driven decision-making and enhance user experience.

Kubernetes Canary Deployment #1 Gitlab CI

Level Up Coding

We will use a manual approach and alter/create core-Kubernetes resources to perform a Canary deployment. This is mainly for understanding how a Canary deployment works, there are better ways…

All you should know about AB testing

Towards Data Science

All steps you should know to run the AB test correctly. In the rapidly changing data world, AB testing is a tool that helps the Product team test hypotheses and makes data-driven decisions rather tha...

A practical guide to A/B Testing in MLOps with Kubernetes and seldon-core

Towards Data Science

A Practical Guide to A/B Testing in MLOps with Kubernetes and seldon-core How to set up a containerized microservice architecture to run A/B tests Photo by Jens Lelie on Unsplash Many companies are u...

AB testing in Game — analyze using Pty

Analytics Vidhya

AB testing is a popular way to experiment with changes in websites, games, etc. We can see the result in a short time and make decisions accordingly. I recently took several statistics thinking using…...

The Engineering Problem of A/B Testing

Level Up Coding

For the last two years, I’ve worked in an environment where A/B testing is a primary rollout mechanism — a completely new experience for me. Recently, Nicolas Gallagher tweeted 37 words that pretty…

On AB tests and Carryover Effect

Towards Data Science

In the complex world of data-driven decision-making, A/B testing stands out as a powerful tool, helping businesses optimize their strategies and improve user experiences. But what happens when the…

A/B Testing -Implementation -2

Python in Plain English

[IF YOU WANT TO READ MY FIRST ARTICLE , https://medium.com/python-in-plain-english/a-b-testing-implementation-2aeea5f26985 ] A/B testing, also known as split testing, is a statistical method utilized…...

How to Support A/B Testing in Your Python Code

ArjanCodes

In today's video, I am taking a close look at A/B testing and feature flags. A/B tests are a great way to establish what your end user likes. If you just make those decisions based on what you think w...

Building ML Predictive Models and Managing AB Testing with Databricks

Level Up Coding

AB End2end experimentation on Databricks — Part I Introduction In today’s digital landscape, organizations are constantly seeking ways to enhance their products and services by leveraging the power of...

Single-Cell RNA Sequencing: An A/B Testing Tool For Biologists

Towards Data Science

A/B testing is a common practice in the tech industry. Every time a new feature is built, product managers and data scientists put it through the ultimate test of performance — A/B testing. The…

7 A/B Testing Questions and Answers in Data Science Interviews

Towards Data Science

A/B tests, a.k.a controlled experiments, are used widely in industry to make product launch decisions. It allows tech companies to evaluate a product/feature with a subset of users to infer how the…

A/B Testing — Implementation

Python in Plain English

A/B testing, also known as split testing, is a statistical method used to compare two or more variations of a specific element or feature in order to determine which one performs better. It is…