HNN
HNN is a Haskell-based library designed for creating, training, and utilizing feed-forward neural networks. Unlike other libraries, HNN prioritizes simplicity and efficiency, allowing users to implement neural networks without sacrificing performance. The library is fully written in Haskell, ensuring seamless integration with Haskell projects, and is available on Hackage.
Top HNN Alternatives
LambdaNet
This artificial neural network library, implemented in Haskell, enables users to create, train, and utilize neural networks through higher-order functions.
NanoNets
Nanonets AI revolutionizes data processing by extracting valuable insights from various sources such as documents, emails, and databases.
RustNN
RustNN is a user-friendly neural network library in Rust that facilitates the creation of feedforward networks.
deeplearn-rs
Deeplearn-rs is an innovative deep learning software crafted in Rust, showcasing a proof of concept for neural network applications.
Google Deep Learning Containers
Google Deep Learning Containers offer performance-optimized Docker images pre-loaded with essential data science frameworks and tools.
BackpropNeuralNet.jl
Users can effortlessly initialize networks with various configurations, such as 2 inputs, 3 neurons in...
Google Cloud Deep Learning VM Image
Each image includes essential frameworks such as TensorFlow and PyTorch, along with the latest AI...
MGL
It enables developers to implement and experiment with advanced algorithms while benefiting from the expressive...
Amazon EC2 G5 Instances
Equipped with up to 8 A10G Tensor Core GPUs and advanced storage, they optimize training...
Hopfield Networks
This Haskell implementation draws from insights in "Information Theory, Inference, and Learning Algorithms" by David...
Amazon EC2 P4 Instances
Utilizing NVIDIA A100 Tensor Core GPUs, these instances achieve remarkable throughput and low-latency networking at...
MLPNeuralNet
Leveraging Apple's Accelerate Framework, it facilitates the seamless integration of trained models for accurate predictions...
Amazon EC2 P5 Instances
They accelerate solutions by up to 4x and reduce ML training costs by 40%...
Multi-Perceptron-NeuralNetwork
It excels in product recommendations, user behavior analysis, and data mining...
Top HNN Features
- Full-Haskell implementation
- Simple network creation
- Efficient training algorithms
- Customizable architectures
- Lightweight library design
- Active GitHub repository
- Easy installation via Hackage
- User-friendly documentation
- Support for feed-forward networks
- Open-source collaboration opportunities
- Minimal performance overhead
- Example usage provided
- Compatibility with GHC 6.8+
- Supports uvector package
- Community engagement via mailing list
- Easily extensible codebase
- Clear separation from C libraries
- Focus on neural network simplicity.
Top HNN Alternatives
- LambdaNet
- NanoNets
- RustNN
- MEGA
- deeplearn-rs
- Google Deep Learning Containers
- BackpropNeuralNet.jl
- Google Cloud Deep Learning VM Image
- MGL
- Amazon EC2 G5 Instances
- Hopfield Networks
- Amazon EC2 P4 Instances
- MLPNeuralNet
- Amazon EC2 P5 Instances
- Multi-Perceptron-NeuralNetwork
