Model Versioning - Learn Data Science with Travis

👥 Edge#153: ML Model Versioning

TheSequence

In this issue: we discuss ML Model Versioning; we explore how Uber backtests and versions forecasting models at scale; we overview Lyft’s Amundsen, an open-sourced data discovery and versioning platfo...

Semantic Versioning

Better Programming

Demystifying SemVer and avoiding “dependency hell” Continue reading on Better Programming

Versioning a system

Analytics Vidhya

Whenever we need to do some API changes that are not backward compatible ie: request params/headers or response object’s structure is changed We don’t usually face many issues with the websites as we…...

Model Rollbacks Through Versioning

Towards Data Science

The Walmart Rollback isn’t the only kind that can save you money Using Model Rollbacks Is Fun! There’s general consensus in the Machine Learning community that models can and have made biased decisio...

Version Control Your ML Model Deployment With Git using Modelbit

Towards Data Science

Develop, deploy, and track! Photo by Yancy Min on Unsplash Introduction Version control is critical to all development processes, allowing developers to track software changes (code, configurations, ...

Data Versioning: All You Need to Know

Towards Data Science

Introduction to Data Versioning with LakeFS command line. lakeFS introduces git-level manageability of your data and introduces CLI and UI interfaces to work with

Version Control ML Model

Towards Data Science

Machine Learning operations (let’s call it mlOps under the current buzzword pattern xxOps) are quite different from traditional software development operations (devOps). One of the reasons is that ML…...

Version Controlling in Practice: Data, ML Model, and Code

Towards Data Science

Version control is a crucial practice! Without it, your project may become disorganized, making it challenging to roll back to any desired point. You risk losing critical model configurations, weights...

Versioning and Labeling — Better Together

Towards Data Science

The key to building powerful machine learning models is learning “the right things from the right data.” Just as we humans constantly take in new information and update what we think about the world…

Branches Are All You Need: Our Opinionated ML Versioning Framework

Towards Data Science

A practical approach to versioning machine learning projects using Git Branches that simplifies workflows and organises data and models TL;DR A simple approach to versioning machine learning projects...

Use semantic versioning

Java Best Practices

Semantic versioning is a well-specified convention used by many software projects, although admittedly the extent to which the convention is followed can vary considerably between projects. In essence...

Versioning Serializers

Level Up Coding

How to version serializers to ensure a smooth transition when deploying changes to many microservices in distributed system.

An Introduction to Semantic Versioning

Level Up Coding

Semantic versioning is a system to help developers, project managers, and consumers have a universal way of understanding the release process. Semantic versioning is some guidelines so that we can…

Versioned Data Management System Design

Level Up Coding

Introduction Previously, I introduced a distributed ledger system . From a technical level, I explained how to build a data store that supports version history consistently. Expanding on this, this po...

Introduction to Data Version Control

Towards Data Science

Any production-level system requires some kind of versioning. A single source of current truth. Any resources that are continuously updated, especially simultaneously by multiple users, require some…

Hangar Tutorial (2/2): Training a Model with the versioned data

Towards Data Science

In the last tutorial, we introduced Hangar, a python library that helps you version control data. Well, data is the new oil and properly managing and streaming your dataflow is vital for your…

Model Versioning done right: Making your Scikit-learn models reproducible with ModelDB 2.0

Analytics Vidhya

At Verta, we ran our first ModelDB 2.0 webinar last week and it was a lot of fun. This blog post is a recap of the hands-on tutorial part of the webinar. For the full webinar content, check out the…

Use semantic versioning

Java Best Practices

Semantic versioning is a well-specified convention used by many software projects, although admittedly the extent to which the convention is followed can vary considerably between projects. In essenc...

The DVC Guide: Data Version Control For All Your Data Science Projects

Towards Data Science

Become familiar with data versioning just like code versioning Continue reading on Towards Data Science

Introduction to DVC: Data Version Control Tool for Machine Learning Projects

Towards Data Science

Git is a powerful tool for version control. It allows you to go back and forth between different versions of your code without being afraid of losing the code you change. As a data scientist, you…

Why Versioning Is Important and How To Do It Properly

Better Programming

You might be wondering what a number on software, a game, or an application means. Something like 11.2.3 or maybe 10.4.3.2arm64. These are the numbers of the version that the application is currently…...

How to detect an obsolete model?

Analytics Vidhya

How to detect an obsolete model?. Did you ever heard about Covariate Drift? In any case, this article will introduce you what it is and how it may be used to get you….

Application Versioning Strategies

Javarevisited

There are many ways to version applications. Some of them appeared a long time ago and have little sense in web development. Nevertheless, they continue to be used. In this article, we will consider t...