HNN

A Haskell Neural Network library for deep learning.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is HNN?

HNN is a Haskell-based neural network library that provides tools and functionalities to build and train deep learning models. It's particularly useful for developers interested in leveraging Haskell's strong typing and functional programming features for machine learning tasks.

Key differentiator

HNN stands out as one of the few neural network libraries that fully integrates with Haskell, offering developers a functional programming approach to machine learning.

Capability profile

Strength Radar

Functional progr…Integration with…Support for vari…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Functional programming approach to neural networks

Integration with Haskell's ecosystem for data processing and analysis

Support for various deep learning models

Fit analysis

Who is it for?

✓ Best for

Developers who prefer functional programming for building neural networks

Teams working on Haskell projects that require integration with machine learning models

✕ Not a fit for

Projects requiring real-time performance critical applications where Haskell might not be the best choice

Users looking for a more mature and widely adopted deep learning framework like TensorFlow or PyTorch

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Next step

Get Started with HNN

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →