Below you'll find a list of all posts that have been categorized as “Open Source”
This blog post summarizes my work done during the Google Summer of Code 2017. My task was to implement topic modeling visualizations which could help users to interactively analyze their topic models and get the best out of their data. I worked on adding two types of visualizations: 1. To monitor the training process of LDA with the help of …
In this blog I want to tell you what it takes to organize an open source coding sprint – find a venue, set an agenda and then actually run it.
If you’ve learned how to train topic models in Gensim, but aren’t able to get satisfying results, then we have a new tutorial that will help you get on the right track on GitHub. Primarily, you will learn some things about pre-processing text data for the LDA model. You will also get some tips about how to set the parameters …
Author-topic models promise to give data scientists a tool to simultaneously gain insight about authorship and content in terms of latent topics. The model is closely related to Latent Dirichlet Allocation (LDA). Basically, each author can be associated with multiple documents, and each document can be attributed to multiple authors. The model learns topic representations for each author, so that …
I was very happy to visit India this October to run three Gensim coding sprints, give workshops and visit PyCon India conference. Many thanks to our Incubator programme student Devashish Deshpande for being my host. PyCon India Pycon India was a very friendly event of 500 attendees with workshops on Friday and conference talks over Saturday and Sunday. My favorite PyCon moment was the keynote …
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