In this project you are going to develop your own word embedding utilities in Julia using APIs like
Word2Vector ([login to view URL]) and TextAnalytics
([login to view URL]). You need also to experiment with your developed utilities and
demonstrate its usefulness and accuracy. Your utilities need to be useful for in depth applications like:
Compute similar words: Word embedding is used to suggest similar words to the word being subjected
to the prediction model. Along with that it also suggests dissimilar words, as well as most common
Create a group of related words: It is used for semantic grouping which will group things of similar
characteristic together and dissimilar far away.
Feature for text classification: Text is mapped into arrays of vectors which is fed to the model for
training as well as prediction. Text-based classifier models cannot be trained on the string, so this will
convert the text into machine trainable form. Further its features of building semantic help in textbased classification.
Document clustering is another application where word embedding is widely used
Natural language processing: There are many applications where word embedding is useful and wins
over feature extraction phases such as parts of speech tagging, sentimental analysis, and syntactic
With this project you will get experience and knowledge of word embedding and textual analytics in Julia.
3 freelancer chào giá trung bình$230 cho công việc này
hi, we have developed more projects in julia. here we ll analysis to do the work deeply. if you have any doubts, kindly contact through chat. Thank you.