ranon-rat/neural-mines-sweeper
Im back bitches
This project helps players make better decisions in Minesweeper by using a neural network to analyze the board. It takes the current state of a Minesweeper board as input and suggests which cells are safest to click or most likely to contain a mine. This tool is for anyone who enjoys playing Minesweeper and wants to experiment with AI-assisted gameplay.
Use this if you are a Minesweeper player curious about how machine learning can be applied to game strategy, or if you're a developer looking for a basic example of a neural network applied to a simple game.
Not ideal if you're looking for a highly accurate, competitive Minesweeper AI or a production-ready machine learning model, as this project is primarily for experimentation and learning.
Stars
8
Forks
—
Language
Go
License
—
Category
Last pushed
Mar 09, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ranon-rat/neural-mines-sweeper"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
SPFlow/SPFlow
Sum Product Flow: An Easy and Extensible Library for Sum-Product Networks
gomlx/gomlx
GoMLX: An Accelerated Machine Learning Framework For Go
montanaflynn/stats
A well tested and comprehensive Golang statistics library package with no dependencies.
mattn/go-tflite
Go binding for TensorFlow Lite
james-bowman/sparse
Sparse matrix formats for linear algebra supporting scientific and machine learning applications