word2vec
Word2vec is an unsupervised machine learning model which is able to capture semantic information from the text it is trained on. The model is based on neural networks. Several large organizations like...
1 Helmi 201931min
Authorship Attribution
In a recent paper, Leveraging Discourse Information Effectively for Authorship Attribution, authors Su Wang, Elisa Ferracane, and Raymond J. Mooney describe a deep learning methodology for predict whi...
25 Tammi 201950min
Very Large Corpora and Zipf's Law
The earliest efforts to apply machine learning to natural language tended to convert every token (every word, more or less) into a unique feature. While techniques like stemming may have cut the numbe...
18 Tammi 201924min
Semantic search at Github
Github is many things besides source control. It's a social network, even though not everyone realizes it. It's a vast repository of code. It's a ticketing and project management system. And of course...
11 Tammi 201934min
Let's Talk About Natural Language Processing
This episode reboots our podcast with the theme of Natural Language Processing for the next few months. We begin with introductions of Yoshi and Linh Da and then get into a broad discussion about natu...
4 Tammi 201936min
Data Science Hiring Processes
Kyle shares a few thoughts on mistakes observed by job applicants and also shares a few procedural insights listeners at early stages in their careers might find value in.
28 Joulu 201833min
Holiday Reading - Epicac
Epicac by Kurt Vonnegut.
25 Joulu 201821min
Drug Discovery with Machine Learning
In today's episode, Kyle chats with Alexander Zhebrak, CTO of Insilico Medicine, Inc. Insilico self describes as artificial intelligence for drug discovery, biomarker development, and aging research. ...
21 Joulu 201828min
