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Making Pictures 3D using Context-aware Layered Depth Inpainting

Making Pictures 3D using Context-aware Layered Depth Inpainting

Several Chinese Ph.D. students wrote a PyTorch program that can turn your holiday pictures into 3D sceneries. They call it 3D photo inpainting. Here are some examples And here’s the new method compares to previous techniques: Here are several links to more detailed resources: [Paper] [Project Website] [Google Colab] [GitHub] We propose a method for … Continue reading Making Pictures 3D using Context-aware Layered Depth Inpainting

Become a data-driven Sommelier by text mining wine reviews

Become a data-driven Sommelier by text mining wine reviews

Aleszu Bajak at Storybench.org published a great demonstration of the power of text mining. He used the R tidytext package to analyse 150,000 wine reviews which Zach Thoutt had scraped from Wine Enthusiast in November of 2017. Aleszu started his analysis on only the French wines, with a simple word count per region: Next, he applied TF-IDF to surface the … Continue reading Become a data-driven Sommelier by text mining wine reviews

Text Mining: Pythonic Heavy Metal

Text Mining: Pythonic Heavy Metal

This blog summarized work that has been posted here, here, and here. Iain of degeneratestate.org wrote a three-piece series where he applied text mining to the lyrics of 222,623 songs from 7,364 heavy metal bands spread over 22,314 albums that he scraped from darklyrics.com. He applied a broad range of different analyses in Python, the code of which … Continue reading Text Mining: Pythonic Heavy Metal

Variance Explained: Text Mining Trump’s Twitter – Part 2

Variance Explained: Text Mining Trump’s Twitter – Part 2

Reposted from Variance Explained with minor modifications. This post follows an earlier post on the same topic. A year ago today, I wrote up a blog post Text analysis of Trump’s tweets confirms he writes only the (angrier) Android half. My analysis, shown below, concludes that the Android and iPhone tweets are clearly from different people, posting … Continue reading Variance Explained: Text Mining Trump’s Twitter – Part 2

Variance Explained: Text Mining Trump’s Twitter – Part 1: Trump is Angrier on Android

Variance Explained: Text Mining Trump’s Twitter – Part 1: Trump is Angrier on Android

Reposted from Variance Explained with minor modifications. Note this post was written in 2016, a follow-up was posted in 2017. This weekend I saw a hypothesis about Donald Trump’s twitter account that simply begged to be investigated with data:  Follow Todd Vaziri  ✔@tvaziri Every non-hyperbolic tweet is from iPhone (his staff). Every hyperbolic tweet is from … Continue reading Variance Explained: Text Mining Trump’s Twitter – Part 1: Trump is Angrier on Android

Harry Plotter: Celebrating the 20 year anniversary with tidytext and the tidyverse in R

Harry Plotter: Celebrating the 20 year anniversary with tidytext and the tidyverse in R

It has been twenty years since the first Harry Potter novel, the sorcerer’s/philosopher’s stone, was published. To honour the series, I started a text analysis and visualization project, which my other-half wittily dubbed Harry Plotter. In several blogs, I intend to demonstrate how Hadley Wickham’s tidyverse and packages that build on its principles, such as tidytext (free book), have taken programming in R to an … Continue reading Harry Plotter: Celebrating the 20 year anniversary with tidytext and the tidyverse in R