From 562200ecf3b1e44a55f741fb8b56c4d3dbd283d0 Mon Sep 17 00:00:00 2001 From: Jack Dermody Date: Mon, 28 Aug 2023 08:05:04 +1000 Subject: [PATCH] updated readme --- README.md | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index c48156d6..fc02e151 100644 --- a/README.md +++ b/README.md @@ -1,18 +1,20 @@ ![image](https://user-images.githubusercontent.com/1952388/177148366-bb4f2d2f-92af-4f60-a0de-ce5e3b08f135.png) -Bright Wire is an extensible machine learning library for .NET with optional MKL and GPU support (via CUDA). +*Bright Wire* is an extensible machine learning library for .NET with optional MKL and GPU support (via CUDA). ## Getting Started -Bright Wire is a .net 7 class library. +*Bright Wire* is a .net 7 class library. The previous .net 4.6 version can be found here: https://github.com/jdermody/brightwire-v2 -Bright Wire runs "out of the box" for CPU based computation. For GPU based computation, you will need to install +*Bright Wire* runs "out of the box" with its own vectorised linear algebra library. + +If you have a NVIDIA GPU then you can also use GPU based computation. You will need to install [NVIDIA CUDA Toolkit 12](https://developer.nvidia.com/cuda-downloads) (and have a [Kepler or better NVIDIA GPU](https://en.wikipedia.org/wiki/CUDA#GPUs_supported)). -To enable higher performance CPU based computation, Bright Wire also supports the Intel Math Kernel Library (MKL). +To enable higher performance CPU based computation on Intel hardware, *Bright Wire* also supports the Intel Math Kernel Library (MKL). ## Tutorials @@ -52,7 +54,7 @@ Install-Package BrightData.Cuda ## Features -### Connectionist aka "Deep Learning" +### Neural Networks * Feed Forward, Convolutional, Bidirectional and Sequence to Sequence (seq2seq) network architectures * LSTM, GRU, Simple, Elman and Jordan recurrent neural networks * L2, Dropout and DropConnect regularisation