Systems | Development | Analytics | API | Testing

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Bringing ML Pipelines to Production - Challenges & Solutions - MLOPs Live #1 - With S&P Global

The session — featuring Ganesh Nagarathnam, Director Analytics & ML Engineering at S & P Global Market Intelligence, and Yaron Haviv, Co-Founder and CTO at Iguazio — goes beyond theory, with industry leaders sharing challenges and practical solutions that involve running Al experiments at scale, versioning, delivery to production, reproducibility and data access.

How to Save Costs (& Time) on Bringing AI to Production - MLOps Live #2 - With Quadient

The session — featuring Jason Evans, Director of DXP Innovation at Quadient, and Yaron Haviv, Co-Founder and CTO at Iguazio — goes beyond theory, with industry leaders sharing challenges and practical solutions that involve running AI experiments at scale, versioning, delivery to production, reproducibility and data access.

Git-Based CI CD for Machine Learning & MLOps - MLOps Live #3 - With Microsoft & GitHub

The session — featuring David Aronchick, Head of OSS ML Strategy at Microsoft; Marvin Buss, Azure Customer Engineer at Microsoft; Zander Matheson, Senior Data Scientist at GitHub; and Yaron Haviv, Co-Founder and CTO at Iguazio — goes beyond theory, with industry leaders sharing challenges and practical solutions that involve running AI experiments at scale, versioning, delivery to production, reproducibility, and data access.

How to dive into behavioral analysis by grouping your users via cohorts

A cohort is a group of users that share certain event together for a certain period of time (for example: users who make payment for the first time in the last 30 days, or added 7 friends in the last week). In other words, a cohort is a group of people with similar behavioural characteristics. Cohorts let you group your users based on their actions, such as who performed add to cart event in the last 7 days but didn’t perform checkout event. List of users who belong in a cohort is automatically kept up-to-date, and you can segment funnels, retention, user profiles, flows and drill data based on cohorts you create.

Track goal completion rates in your mobile app by using Funnels and discover user activities

Funnels are used to track the goal completion rates of a step by step path inside your application. These goals (steps) are defined as custom events in Countly and you don't need any extra/new API calls if you have already been using custom events. Countly Drill is advanced segmentation feature, available with Enterprise Edition. Drill can be very powerful when it comes to understanding segmented data. This video provides more information and shows how to use Countly Funnels and Drill.

Load testing with Azure Pipelines

If you want to jump straight to installing the marketplace extension, you can find it here. Performance issues can quickly turn expensive. Reasons can vary from unexpected traffic surges, pieces of non-performant code acting as bottlenecks, or misconfigured network components. Integrating load- and performance testing into your CI pipeline will allow you to know about performance degradations early, in most cases, even before it has any impact on your users in the production environment.

Open-Source vs Commercial tools for test automation?

In software testing, open-source tools have existed for quite a while and they will keep existing in the future. New testing frameworks and tools appear every single day, so how do you know what works best for you? Are commercial tools better than open-source alternatives or the other way around? There is no clear answer and “it depends” highly on your needs. Teams are unique and should use whatever tools they want in order to be more efficient, productive, and happy.