Training courses, hackathons, events and jobs for Machine Learning & AI Engineers

👥 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...

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...

Data and Machine Learning Model Versioning with DVC

Towards Data Science

DVC: It’s a Git, but for Our Data and ML Model Continue reading on Towards Data Science

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...

API Versioning : the guide

Javarevisited

API Versioning : the guide In web application development, REST APIs play a central role in allowing clients — mobile applications, web front-ends, or partners — to access data and services. However,...

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...

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...

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, ...

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...

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…

Model Validation

Kaggle Learn Courses

You've built a model. But how good is it? In this lesson, you will learn to use model validation to measure the quality of your model. Measuring model quality is the key to iteratively improving your ...

Model Validation

Kaggle Learn Courses

You've built a model. But how good is it? In this lesson, you will learn to use model validation to measure the quality of your model. Measuring model quality is the key to iteratively improving your ...