Hot answers tagged

3

MNIST is not an interesting data set. You use MNIST to learn how to do machine learning that you will you on interesting data sets. Thus... If you just want to figure out how to do the Keras code for an image classification problem, feel free to use 0/1 encoding of white vs not-white spaces in the images. It might lower the computational demands so you can ...


1

Mann Whitney U Test (Wilcoxon Rank Sum Test) shall enable us to compare the ratings on System A and system B. This test compares the shape of each population and tells whether the two samples differ. If the shape is same, the null hypothesis is accepted. If the shape of one of distribution is different from the another distribution, the two systems have a ...


1

You need to perform some tests to identify the appropriate statistical measure for comparing the two distributions accurately. For each group/system, run a normality test to make sure that you are not dealing with an ultra exotic distribution to which central limit theorem does not apply (very unlikely). Calculate the variance for each group, in order to ...


1

In case you want some state-of-the-art technique, you can implement a neural machine translation model with attention, as fully described in this course with Google members libraries like Trax. In case of short texts, you can still use sequence-to-sequence models without attention, but the attention mechanism prevents you from suffering the vanishing ...


1

Text reversal task is a typical toy problem, not only for Transformers but for seq2seq models in general. In that task, you take a piece text in whatever language as source, and the words in reverse order as target.


1

Therefore, how should the ground truth for the person's bounding box should be encoded? The bounding boxes are defined by the normalized coordinate of the bounding box center. It should be represented as a single line in a text file as: <object-class> <x> <y> <bb_width> <bb_height> Given 3 classes: 0 full-image 1 top-left-...


1

If the undesired characters are constant as in the example, like ce7380 where the ce is unwanted, one may try the following: library(stringr) df <- df %>% mutate_at("INTERACTOR_A", str_replace, "ce", "") This instructs R to perform the mutation function in the column INTERACTOR_A and replace the constant ce with ...


1

There is a design pattern call "strangler" that might be applicable. The strangler design pattern leaves all legacy systems in place and migrates piece-by-piece to a single, updated system. It does this by creating a proxy interface that routes requests to either legacy system or the updated system. As the migration happens, the proxy routes more ...


Only top voted, non community-wiki answers of a minimum length are eligible