The ANT PC PHEIDOLE RL400 workstation delivers the performance and speed to power through tasks—with up to 6 cores per CPU, the latest generation of Intel and AMD processing combines blazing-fast memory with dual M.2 storage support.
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Our solutions are plug & play without any complex installation
Our workstations are extensively customisable as per your requirements which makes your Ant PC Workstation PC unique.
Ant PC Workstations are equipped with performance cooling solutions so that you could peak your components without stressing them out.
Our Workstation PCs are stress tested with advance burn-in test techniques so as ensure that you get reliability and performance.
Every Ant PC comes with standard 3 Years RTB warranty or 3 Years of optional On-Site warranty at minimal cost that covers all your components and gives you peace of mind.
Ant PC workstations comes with lifetime technical support which even exists even after warranty period that adds to the hassle free experience for you with Ant PCs
To ensure that our Workstation PC exceeds the industry quality standards we have more than 80 quality check points in place so that you get best of the best.
ANT PC PHEIDOLE RL400 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 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.
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