Vesa Saarinen, Software developer, Portfolio

Neural networks and automatic differentation in Java

Neural networks with automatic differentiation and backpropagation in Java from scratch.

Why: Learn about machine learning, gradient descent, neural networks.

Github: https://github.com/vesas/java-nn

Tech: Java

Omastoppi.fi

Web/mobile application for quickly viewing departure times for nearby public transport stops. Data fetched realtime from the HSL GraphQL API.

Why: Learn React/Next.js, and create an application which can be used quickly when on the go on the HSL region.

Release: https://www.omastoppi.fi/

Github: https://github.com/vesas/nextjs-omastoppi

Tech: Typescript, React/Next.js, Tailwind CSS, GraphQL

Econstats.eu

Application which charts the major macroeconomic indicators for the EU and US areas. Data is fetched every day from the Eurostat and FRED APIs.

Why: Learn more about AWS services. Create an economy "dashboard" for myself.

Release: https://econstats.eu

Architecture: https://econstats.eu/architecture

Tech: Python, AWS Lambda, AWS S3, AWS DynamoDB, AWS API Gateway, AWS Cloudformation

WFC generator

In game development WFC (Wave Function Collapse) is used for generating output based on a set of tiles and rules. This output can then be used for different purposes, like level or texture generation. Here I'm creating textures. This is a simple Java implementation of Wave Function Collapse algorithm where the rules are defined in code.

Why: Complex result from simple rules.

Github: https://github.com/vesas/simple-wfc

Tech: Java, LibGDX, Gradle