High performance 2U server with Dual Intel Xeon CPUs, 16 DIMMs, 8 hot-swap HDD bays and option of adding up to 4 GPUs which can be either Nvidia Tesla cards or Nvidia Quadro series cards is perfect for AI and Deep Learning projects.
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ANT PC PHEIDOLE XE4210X is Built For Leading AI, Deep Learning & Machine Learning Applications
Caffe is a deep learning framework made with expression, speed, and modularity in mind. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices.
Theano is a numerical computation library for Python. In Theano, computations are expressed using a NumPy-esque syntax and compiled to run efficiently on either CPU or GPU architectures. Theano is an open source project[2] primarily developed by a machine learning group at the Université de Montréal.
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.
Keras is a high-level neural networks library, written in Python and capable of running on top of either TensorFlow or Theano. It was developed with a focus on enabling fast experimentation.
Tensors and Dynamic neural networks in Python with strong GPU acceleration.