Series

Understanding Deep Learning by Building It in Rust

Learn deep learning by building it from scratch in Rust using Burn only for tensors. We’ll implement activations, losses, backprop, and optimizers step by step to understand how neural networks truly work.

Introduction
The best way to understand how things work is to build them by yourself. I believe implementing deep learning in Rust is a great way to develop a strong understanding in deep learning while enjoying t
Oct 19, 20251 min read1
Part 1: Tensors
As you begin your implementation, the first thing you will encounter is the tensor. In order to know how deep learning works, you must understand this fundamental structure. A tensor is simply a multi
Oct 19, 20254 min read1
Part 2: Generating Training Data
Now that we've seen tensors, it's time to start building the deep learning process. The first thing we need is a dataset for training. Instead of using pre-made dataset, we are going to build our own
Nov 6, 20254 min read2
Part 3: Building a Neural Network Layer
Now that our dataset is ready, we are ready to start building the components of our neural network. But before wejump into the code, let’s pause for a moment to define what deep learning actually is.
Dec 6, 20255 min read
Part4: Building a Simple Regression Model and Preparing Training Tensors
So far, we have implemented our dataset, layers, and an initializer. Now, it’s time to combine them and start shaping an actual neural network. Before we get to the code, let’s first walk through the
Feb 24, 202611 min read
Part5: Forward Pass
With our dataset prepared and our model's architecture ready, we are at starting point of deep learning. The first part is the forward pass. In this part, we will implement the entire forward pass fro
Feb 24, 202610 min read

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