? New Article Alert ?

Hey folks! I've just published a new article on robustness in AI: "Adversarial Attacks and Defenses in Machine Learning." Dive into the world of adversarial attacks, explore various defense strategies, and enhance your knowledge of AI security. Don't miss out!

? Read it now: https://medium.com/@slavadubrov/adversarial-attacks-and-defenses-in-machine-learning-1b649791816a

Medium

Adversarial Attacks and Defenses in Machine Learning

In the previous article, “Understanding Machine Learning Robustness: Why It Matters and How It Affects Your Models”, we explored the…

Hey folks! ?
I've spent the last two weeks crafting a blog post on embedding systems, specifically focusing on building and deploying one at Wayfair. If you're curious, give it a read here: Introducing Melange: A Customer Journey Embedding System ?

Don't worry, I'm still working on the robustness series, so keep an eye out for updates! ?

About Us

Introducing Melange: A Customer Journey Embedding System for Improving Fraud and Policy Abuse Detection

Let’s look at how we at Wayfair use custom embedding models to capture complex customer behavior patterns for advanced Fraud prevention.

? Hey My Telegram Folks!
It's been quite a while since we last connected – a whole year, in fact. Time really flies, doesn't it? ? I'm pleased to announce that I'm back and launching a new series of blog posts on Machine Learning Robustness.

We'll begin with an introduction to the general concepts and, as we progress, dive into practical, hands-on lessons with theory and code examples. ??
If you are interested check out the first post here: Understanding Machine Learning Robustness: Why It Matters and How It Affects Your Models

Let's make our machine learning models as robust as my ability to stay silent on Telegram for a year! ? Stay tuned for more! ?

Medium

Understanding Machine Learning Robustness: Why It Matters and How It Affects Your Models

Balancing Robustness and Accuracy: The Key to Trustworthy Machine Learning Models

Interactive visual introduction to the precision & recall tradeoff

MLU-Explain

Precision and Recall

A visual introduction to Precision, Recall, and the F1-score in machine learning.

Must read article about Data Distribution Shifts and Monitoring

Chip Huyen

Data Distribution Shifts and Monitoring

Note: This note is a work-in-progress, created for the course CS 329S: Machine Learning Systems Design (Stanford, 2022).

If you, like me, always struggle setting up your new MacBook device, take a look at my quick 10-step guide on how I set up macOS for my daily DS routine:
Medium story

Medium

Setting up a MacBook as Data Science Specialist

I believe this story is familiar to everyone. You get a new MacBook and try to recall what exactly do you need there. This happened to me…

Best Practices on Recommendation Systems by Microsoft

- Github

GitHub

GitHub - recommenders-team/recommenders: Best Practices on Recommendation Systems

Best Practices on Recommendation Systems. Contribute to recommenders-team/recommenders development by creating an account on GitHub.

Applications of Graph Neural Networks

Medium

Applications of Graph Neural Networks (GNN)

In two previous articles, we present an overview of the GCN and GNN networks. In our final article, we will cover their possible…

Netron - the crossplatform tool for visualizing deep learning models:

- Github

GitHub

GitHub - lutzroeder/netron: Visualizer for neural network, deep learning and machine learning models

Visualizer for neural network, deep learning and machine learning models - GitHub - lutzroeder/netron: Visualizer for neural network, deep learning and machine learning models