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Need CXXNET experts to help with a fast, concise, distributed deep learning framework?   Hire Experfy freelance CXXNET experts capable of configuring CXXNET, setting Data Input Iterator, and configuring the network, and setup each layer. They can also set up parameters such as learning rate, momentum for learning procedure, other parameters for the neural network, related to device selection, running control, and convert the pre-trained model in Caffe to CXXNET. They can modify the configuration to adjust your environment settings. Familiar with basic steps to using convolution neural network, our CXXNET experts know how to use CXXNET to solve a real kaggle problem by using CXXNET, train an AlexNet for ImageNet task, train kaggle bowl on multi-machines, and pre-trained model with all configurations. Further, they can write expressions for machine learning using MShadow which is the lightweight CPU/GPU Tensor template library for CXXNET, and also write numpy-style template expressions to extend the Template Library.

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