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Great, but the problem with these summaries is no real-world data/use-case. An actual business case example with code is easier to comprehend for less math-incl
by rrggrr 8y ago
Great, but the problem with these summaries is no real-world data/use-case. An actual business case example with code is easier to comprehend for less math-inclined folks.
- jackallis 8y agoi agree, especially for beginners.
- deleted 8y ago[deleted]
- cr0sh 8y agoThe problem with that is these kinds of simplified "how it works" neural net examples don't scale for real world problems - especially when using an interpreted language like Python. Even a simple but useful scenario like the MNIST number recognition system would probably run "dog-slow" on such a neural network, given the number of input nodes, plus the size of the hidden layer - the combinatorial "explosion" of edges in the graph, all the processing needed during backprop and forwardprop... It might be doable with C/C++ - but it still won't run as well as it could. These examples are really just meant as teaching tools; they are the bare-bones-basics of neural networks, to get you to understand the underlying mechanisms at work (actually, the XOR network is the real bare-bones NN example, because it requires so few nodes, that it can be worked out by pencil and paper methods). Real-world implementations are best done using more advanced libraries and tools, like Tensorflow and Keras, or similar (and moving to C/C++ and/or CUDA if even more processing power is needed).
- ldng 8y agoMaybe you missed the disclaimer ? "The code below is intended to be simple and educational, NOT optimal."
- Shorel 8y agoWith neural networks, real-world data and real-world use-cases have expensive hardware requirements. You can, however, try this service for free during the first two months: https://aws.amazon.com/blogs/aws/sagemaker/ https://aws.amazon.com/blogs/aws/sagemaker/ (I am not affiliated with AWS and I have not used SageMaker) You can also read the DeepMind blog to find out the latest state-of-the-art real-world usage of Neural Networks.