Articles
AI with Metaverse will change the world in 2030 Paid Members Public
Integrating AI with the Metaverse is expected to revolutionize how we interact with technology and each other. In 2030, this synergy is projected to transform the world and open up new opportunities in various fields, ranging from entertainment to healthcare and education.
A Guide to the YOLO Family of Computer Vision Models Paid Members Public
YOLO (You Only Look Once) is an advanced algorithm that can detect and recognize various objects in a picture in real-time, faster and more accurately than any other algorithm. The YOLO family is advancing, step-by-step, and every update adds to its potential.
Why Privacy is a Thing of the Past in the AI-Powered Classroom Paid Members Public
Artificial intelligence (AI) has the potential to revolutionize higher education, offering personalized learning experiences and increasing efficiency. However, as with any technology, there are also concerns about privacy and discrimination that must be addressed. One major concern is the issue of privacy in the collection and use of student data.
AVL Binary Tree Operations Paid Members Public
In this article, the author described AVL trees and operations you can perform on them, such as inserting a node in different variants (for example, left, right or right, right).
Bringing GitOps to ML with dstack Paid Members Public
GitOps is a DevOps paradigm that helps teams ship software more quickly by applying things like version control, collaboration, compliance, and CI/CD. In ML, GitOps is still at the trial stage and isn’t adopted at scale yet. This post sums up some of the ideas around GitOps and
“You Can’t Predict the Errors of Your Model”… Or Can You? Paid Members Public
NannyML has released DLE, an algorithm able to predict the MAE and the MSE of your regression model, in the absence of the ground truth In a previous article, we have seen how to predict the performance of your classification model, before the ground truth is available. This is super
Data Science and Machine Learning from Scratch [And More] Paid Members Public
We believe that any data scientist and ML professional should never stop learning. In this post, we provide an overview of the best resources and courses you can use to start digging in.
