This week in AI & Machine Learning: Data-centric AI, creating better virtual backgrounds, MLCon 2.0, No-code deep learning, and more.

Authors Note: 

I’m hosting a No-code Deep Learning for Faster Computer Vision workshop on February 23rd. You can register for free on Eventbrite.

Artificial Intelligence News:

Is It Time for a More Data-Centric Approach?

This interview with AI pioneer Andrew Ng focuses on using data-centric machine learning, which focuses more on datasets instead of the code or model implementation. Read how data-centric AI can help solve big issues on IEEE.

5 Questions to Ask Before Getting Started with Data Annotation

 

Getting started with data annotation for computer vision can be challenging. This post covers data annotation for different model types, common mistakes, and how to use AI-powered tools to speed up the process. Read how to get started with data annotation here.

Creating Better Segmentation Models for Virtual Backdrops and AR with Computer Vision.

Chances are you’ve used a virtual background while video chatting at some point, but you may not have considered how tricky it can be to engineer. Read how Meta improves background blurring, virtual backgrounds, and augmented reality applications on their official AI blog.

MLCon 2.0 — The AI and ML Developers Conference

The lineup for MLCon 2.0 looks pretty impressive with over 40 industry-leading ML experts! The free AI conference runs through February 22–23, 2022. You can register at cnvrg.io/mlcon

How Will the Super Bowl Change the Future of Venues?

Sports venues are changing to make game-day experiences better. Did you know that SoFi Stadium is the first venue in the United States to implement digital twin technology? Read more in this post: How Will Super Bowl LVI Change the Future of Fandom?

No-code Deep Learning for Faster Computer Vision [FREE Workshop]

As I mentioned in the Authors note, I’m excited to teach this workshop on February 23rd at 5:30 pm (PST)! We’ll cover how to build your own computer vision models from start to finish with no code — from data annotation, model training and, deployments. Register for free on Eventbrite.

I’ll see you next week! You can join the discussion on the AI for ALL Slack.

About the Author & Plainsight:

Sage Elliott — Lead Developer Evangelist. Helping Plainsight make AI approachable for everyone.

Plainsight’s vision AI platform streamlines the end-to-end machine learning process. From data annotation through deployment, customers quickly create and successfully operationalize their own vision AI applications to solve highly diverse business challenges.

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