# convnet

**Repository Path**: jlxing/convnet

## Basic Information

- **Project Name**: convnet
- **Description**: A GPU implementation of Convolutional Neural Nets in C++
- **Primary Language**: Unknown
- **License**: BSD-2-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-05-23
- **Last Updated**: 2022-05-28

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

### Welcome to ConvNet.
ConvNet is a fast C++ based GPU implementation of Convolutional Neural Nets.
- Supports Multi-GPU architectures (Multiple GPUs, Single machine).
- Provides a fast CPU-only feature extractor.

### Installation
[Install guide] (https://github.com/torontodeeplearning/convnet/blob/master/INSTALL)

### Pre-trained Models
Pre-trained models and examples for training and feature extraction are provided for
- [Imagenet Classification (ILSVRC 2013)](https://github.com/torontodeeplearning/convnet/tree/master/examples/imagenet)
- [MNIST](https://github.com/torontodeeplearning/convnet/tree/master/examples/mnist)

### Tutorials
Coming soon.

### Documentation
[here](http://torontodeeplearning.github.io/convnet/docs)