21–30 of 32 posts
Anyone know of any benchmarks on tensorflow that provide a baseline estimate of the expected performance for some off-the-shelf hardware(s)?
https://github.com/soumith/convnet-benchmarks
They place TensorFlow performance on par with Torch (within 10%).
I find it so aggravating that nearly every last ML framework documents their CNN libraries in terms of canned MNIST datasets imported from the library in a preprocessed form. It's always left as a useless exercise for the reader to divine how to generate such a dataset from his/her own data. Examples should be way more general. The starting point shouldn't be: from tensorflow.examples.tutorials.mnist import input_dat…
I find it so aggravating that nearly every last ML framework documents their CNN libraries in terms of canned MNIST datasets imported from the library in a preprocessed form. It's always left as a useless exercise for the reader to divine how to generate such a dataset from his/her own data. Examples should be way more general. The starting point shouldn't be: from tensorflow.examples.tutorials.mnist import input_dat…
I find it so aggravating that nearly every last ML framework documents their CNN libraries in terms of canned MNIST datasets imported from the library in a preprocessed form. It's always left as a useless exercise for the reader to divine how to generate such a dataset from his/her own data. Examples should be way more general. The starting point shouldn't be: from tensorflow.examples.tutorials.mnist import input_dat…
The format for the dataset is here: http://yann.lecun.com/exdb/mnist/ A good exercise would be to figure out how to extract the data and put it into a numpy array. Then you can test on most - if not all - of the frameworks.
This is missing a FizzBuzz example.
Say you need a CNN text classifier algorithm to categorize simple single page documents. So you set one up via TensorFlow, train it with a big dataset, and get it outputting categories with decent accuracy. Could you then use some type of API and query it from a (low traffic) production web app?
Or is it more for the research phase rather than real-time interaction?
Does someone point me in the right direction for using a neural network for prediction (the input will be time series data). All the beginner's tutorials I have seen deal with classification and not prediction.