DEV Community: Sergiy Bondaryev

Solving Mastermind with Maximum Entropy

Sergiy Bondaryev — Tue, 10 Mar 2026 01:40:06 +0000

An article on solving the Mastermind game using information theory.

The idea is to choose guesses that give the most information and reduce the number of possible codes as fast as possible.

With this method the code can be solved in about 4.42 guesses on average across all 1296 possible codes.

What’s covered

How Mastermind feedback works
Why some guesses are more informative
How entropy helps choose the next guess
How the solver works

https://sbondaryev.dev/articles/mastermind-entropy

Chess OCR: From Data to Deployment

Sergiy Bondaryev — Tue, 24 Feb 2026 13:30:59 +0000

This article shows how to recognize chess positions from images and run the entire pipeline directly in the browser.

The approach is to split the board into 64 squares, classify each square independently, and then reconstruct the position for analysis.

What’s covered:

Creating a custom dataset of chess diagrams
Learning representations with SimCLR and Autoencoder
Training a CNN to classify chess pieces

Running preprocessing and inference client-side with Pyodide and ONNX Runtime Web

https://sbondaryev.dev/articles/chess-ocr

Why Neural Networks Need He Init, Clipping, and Momentum

Sergiy Bondaryev — Tue, 27 Jan 2026 22:12:22 +0000

I built an interactive tutorial that shows why neural networks fail without proper initialization and optimization techniques. Here's what you'll find:

Live code editor where you can watch networks train in real-time on x²
Step-by-step progression from linear models → ReLU → deep networks
Visual demonstrations of gradient explosion and dying ReLU problems
Interactive examples showing how each fix (He init, clipping, momentum) solves specific issues
Final section on vectorization and why frameworks use matrix operations

The approach is hands-on: start with a broken 2-layer network that hits NaN, then add fixes one at a time while watching the loss curve and predictions update. You can swap x² for cos(3x) or tweak hyperparameters to see how networks behave under different conditions.

Check it out at https://sbondaryev.dev/articles/he-init-clipping-momentum

Interactive Big O Notation Guide

Sergiy Bondaryev — Fri, 09 Jan 2026 23:28:46 +0000

I created an interactive guide to help build intuition for recognizing time complexity from code patterns.
What's inside:

Live code editor with visual feedback as you adjust input sizes
Examples ranging from O(1) to O(n!) with interactive visualizations
Coverage of core principles like "constants drop out" and "nested operations multiply"
Master Theorem breakdown with practical examples
Real algorithm analysis (merge sort, binary search, etc.)

The idea is simple: add op() markers to your code and watch the complexity curves appear as n increases. You can experiment with loops, recursion, or drop in your own algorithms to see how they scale.
Built with Next.js and deployed at https://sbondaryev.dev/articles/big-o-notation.

Feedback welcome!