Java Enthusiast Builds AI Library from Scratch: A Deep Dive into Deep Learning Fundamentals
research#deep learning📝 Blog|Analyzed: Feb 16, 2026 07:48•
Published: Feb 16, 2026 06:14
•1 min read
•r/learnmachinelearningAnalysis
This is a fantastic example of a developer taking a hands-on approach to understanding the inner workings of deep learning! Building a complete AI library in pure Java demonstrates a commitment to foundational knowledge, offering a unique perspective on computation graphs and backpropagation. The successful MNIST training with impressive accuracy validates the effectiveness of this educational endeavor.
Key Takeaways
- •The library includes custom tensor implementation, various layers, activation functions, and an Adam optimizer.
- •Reverse-mode automatic differentiation is implemented for backpropagation.
- •The developer successfully trained a CNN on MNIST, achieving ~97% test accuracy after one epoch.
Reference / Citation
View Original"I wanted to better understand how deep learning frameworks work internally, so I built a small AI library from scratch in pure Java."