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 ...

While you can train simple neural networks with relatively small amounts of training data with TensorFlow, for deep neural networks with large training datasets you really need to use CUDA-capable ...

At version r1.5, Google's open source machine learning and neural network library is more capable, more mature, and easier to learn and use If you looked at TensorFlow as a deep learning framework ...

Overview: Python and SQL form the core data science foundation, enabling fast analysis, smooth cloud integration, and ...

Around the Hackaday secret bunker, we’ve been talking quite a bit about machine learning and neural networks. There’s been a lot of renewed interest in the topic recently because of the success of ...

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.

Data science is often cited as one of the main reasons for Python's growing popularity. But while people are definitely using Python for data analysis and machine learning, not many of those using ...

Besides putting a Raspberry Pi to work on a mini Mars rover, it's now going to be a lot easier to use Google's TensorFlow artificial-intelligence framework with the low-powered computer. Developers ...

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