Deep Learning

The Sigmoid Function: From 'e' to Neural Networks
Deep Learning
We use the equation all the time. But where did it actually come from?
Nikhil Dasari
August 27, 202614 min read
Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works
Deep Learning
From one gradient to every gradient
Nikhil Dasari
August 12, 20269 min read
Variational Autoencoders (VAEs) Explained: From Theory to ELBO and the Reparameterization Trick
Deep Learning
A clear, math-first walkthrough of how VAEs learn to generate new data
Vyacheslav Efimov
August 10, 202610 min read
SPP-Net Paper Walkthrough: Breaking the Fixed-Size Constraint
Deep Learning
Learn how Spatial Pyramid Pooling enables CNNs to handle any image size, with a from-scratch PyTorch implementation
Muhammad Ardi Putra
August 10, 202618 min read
Before Q, K, and V: Reconstructing the Transformer
Deep Learning
Many Transformer explainers start with the finished architecture. We ask why it looks the way it does.
Sankar Srinivasan
August 8, 202625 min read
Backpropagation Explained for Beginners (Part 2): There Has to Be a Better Way
Deep Learning
The idea that makes backpropagation possible.
Nikhil Dasari
July 28, 20266 min read
Backpropagation Explained for Beginners (Part 1): Building the Intuition
Deep Learning
Let's discover how neural networks learn, step by step
Nikhil Dasari
July 19, 20269 min read
PANet Paper Walkthrough: When Feature Pyramids Go Bottom-Up
Deep Learning
Understanding how PANet shortens the path between low-level and high-level features
Muhammad Ardi Putra
July 5, 202615 min read
Neural Networks, Explained for Beginners: Start Here If They’ve Confused You
Deep Learning
The intuition behind neural networks and why they need activation functions.
Nikhil Dasari
June 22, 202619 min read
Building a Custom GStreamer Plugin for NVIDIA DeepStream
Deep Learning
Why custom inference in DeepStream?
David Redó Nieto
June 19, 20269 min read