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10/29/2021 10:14:34 AM

👓 Edge#135: Self-Supervised Learning for Computer Vision 

The conclusion of our self-supervised learning series ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌
4/26/2022 11:24:44 AM

🕸 Edge#185: Centralized vs. Decentralized Distributed Training Architectures

In this issue: we overview Centralized vs. Decentralized Distributed Training Architectures; we explain GPipe, an Architecture for Training Large Scale Neural Networks; we explore TorchElastic, a
6/28/2022 11:14:26 AM

🔴🟨 Edge#203: What are Graph Recurrent Neural Networks?

+ what GNNs on Dynamic Graphs; and the exploration of DeepMind's Jraph, a GNN Library for JAX. ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌
6/21/2022 11:24:37 AM

💠 Edge#201: Understanding Graph Convolutional Neural Networks

In this issue: we explain Graph Convolutional Neural Networks; we overview the original GCN Paper; we explore PyTorch Geometric, one of the most complete GNN frameworks available today. Enjoy the
7/26/2022 11:14:27 AM

🤷🏻 Edge#211: What to Test in ML Models

In this issue: we discuss what to test in ML models; we explain how Meta uses A/B testing to improve Facebook's newsfeed algorithm; we explore Meta's Ax, a framework for A/B testing in PyTorch.
8/25/2022 12:14:28 PM

🐙 Edge#220: Dive into Meta AI’s Make-A-Scene, which pushes the boundaries of AI art synthesis

The new model uses text-to-image and image-to-image generation to produce astonishing artistic outputs. ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌