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Deep Learning is a buzzword that will be familiar to most people. It will bring to mind vast arrays of hardware working in tandem. And this was true once, but gone are the days and days of training required for a machine to learn a model. It’s time to rethink how we view Deep Learning.
Here is the benefit of using GPUs. Graphical Processing Units are key elements in modern high-performance computers most commonly used to render 3D graphics in video games, a compute-intensive operation where polygons are drawn to create a virtual world. In short, a GPU is basically a large array of tiny processors that together perform highly parallelized computation. Yes, you are sitting in front of your very own little super-computer right now!
Some tasks, especially sequence processing with recurrent neural nets, are painfully slow on a CPU, even a high-end multicore. Using a GPU will greatly speed up the process, often by 5 to 10 times, over a CPU.
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TensorFlow is an end-to-end platform that makes it easy to build and deploy your Machine Learning models, whether it’s your first time or your hundredth.
TensorFlow lets developers get started quickly and easily with Deep Learning in the cloud. This framework is quickly becoming the industry standard and is widely used in Deep Learning research and App development, especially in the fields of computer vision, natural language understanding, and speech translation.
TensorFlow’s full suite of visualization tools offer a straightforward and user-friendly experience from debugging to application optimization. Images, audio cues, histograms and graphs all make for a great user experience allowing you to focus on training your massive, deep neural networks quickly and easily. No-fuss, no muss.Mobile development
TensorFlow Mobile on Android features a smaller overall footprint and mathematical toolset tailored to smaller models. TensorFlow Mobile is ideal for users with limited or expensive network access.Documentation
TensorFlow is accompanied by access to a vast library of documentation and tutorials that can assist you in developing your AI. Furthermore, TensorFlow has attracted a large user community that actively contributes code and problem-solve on GitHub.