I have a dataset of articles/blogs collected date wise from different political blogs.I want to perform topic modelling on these articles/blogs using NMF, LDA and Kmeans algorithm.
I want to get the following results from these algos :
1) I want to perform topic modelling (TM) on these articles/document for each date separately and wants to identify/see which document belong to which topic after performing these algos.
2) what are the probability distribution of these topics related to each document for each date
3) Basically these articles/blogs have been collected from political blogs,Therefore I want to perform word cloud on each political blog for each [login to view URL], periodically over the time for each political blog I want to see on what topic they are talking about
4) In the end I want to compare the results of all 3 algos and establish the findings in the form of a report
If you can deliver quality work within a reasonable time at a reasonable price, there will definitely be more work for you in the future.
AS YOU BID PLEASE QUOTE YOUR ACTUAL PRICE.
Lastly,This Project is already behind schedule, so time is very important here
24 freelancers are bidding on average $225 for this job
We need to have a Kick off Meeting. Relevant Skills and Experience We need to have a Kick off Meeting. Proposed Milestones $944 USD - Topic Modelling (using NMF,LDA and Kmeans algorithm)
i will be working with python and its ml libraries Relevant Skills and Experience i have experience in machine learning and deep learning too. I have completed 2 internship on ML Proposed Milestones $166 USD - -