It's possible to create neural networks from raw code. But there are many code libraries you can use to speed up the process. These libraries include Microsoft CNTK, Google TensorFlow, Theano, PyTorch ...

Getting computers to recognize objects has been a historically difficult problem in computer science, but with the rise of machine learning it is becoming easier to solve. One of the tools that can be ...

TensorFlow is an open source software library developed by Google for numerical computation with data flow graphs. This TensorFlow guide covers why the library matters, how to use it and more.

Highlights Network engineers are increasingly adopting Python libraries to automate device management, configuration, and monitoring.Tools like Nornir, Netmiko, ...

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Introducing Anaconda, a Python distribution for scientific research. I've looked at several ways you could use Python to do scientific calculations in the past, but I've never actually covered how to ...

Despite some of the inherent complexities of using FPGAs for implementing deep neural networks, there is a strong efficiency case for using reprogrammable devices for both training and inference.

Mix-in programming is a style of software development where units of functionality are created in a class and then mixed in with other classes. This might sound like simple inheritance at first, but a ...