DownloadCURRENNT is a machine learning library for Recurrent Neural Networks (RNNs) which uses NVIDIA graphics cards to accelerate the computations.
The library implements uni- and bidirectional Long Short-Term Memory (LSTM) architectures and supports deep networks as well as very large data sets that do not fit into main memory.
Features
- Uni- and bidirectional Long Short-Term Memory (LSTM) layers with forget gates and peepholes
- Feedforward layers with tanh, logistic sigmoid and softmax activation functions
- Deep neural network architectures supported
- Cached on-line learning from large data sets (training data does not need to fit in main memory)
- Reads training data from NetCDF files
- Gradient descent with momentum
- Supports on-line, batch and hybrid on-line/batch learning
- Minimization of cross-entropy and squared error objectives
- Supports regression and binary/multiclass classification tasks
- Training with input activation noise for improved generalization
- Autosave after each training epoch
Project Samples
License
GNU General Public License version 3.0 (GPLv3)Follow CURRENNT
Other Useful Business Software
FortiGate NGFW identifies and stops advanced threats with powerful application control, malware protection, web filtering, antivirus, and IPS technology. As the attack surface expands, FortiGate provides integrated and automated protection against emerging and sophisticated threats while securing hybrid or multi-cloud environments. Deploy today in Azure Marketplace.
Rate This Project
Login To Rate This Project
User Reviews
-
Great tool for sequence to sequence BLSTM!
-
Works!
-
Good job. Thank you for your sharing.