Adding strings in R
This started out as a ‘hey, I wonder…’ sort of thing, but as usual, they tend to end up as interesting voyages into the deepest depths of code, so I thought I’d write it up and share. Shoutout to @coolbutuseless for proving that a little curiosity can go a long way and inspiring me to keep digging into interesting topics.
Exporting editable plots from R to Excel: making ggplot2 purrr with officer
I was recently confronted to the following problem: creating hundreds of plots that could still be edited by our client. What this meant was that I needed to export the graphs in Excel or Powerpoint or some other such tool that was familiar to the client, and not export the plots directly to pdf or png as I would normally do. I still wanted to use R to do it though, because I could do what I always do to when I need to perform repetitive tasks such as producing hundreds of plots; map over a list of, say, countries, and make one plot per country. This is something I discussed in a previous blog post, Make ggplot2 purrr. So, after some online seaching, I found the {officer} package. This package allows you to put objects into Microsoft documents. For example, editable plots in a Powerpoint document. This is what I will show in this blog post.
Commercial data analytics: An economic view on the data science methods
The most demanding skill in data science is statistical regression analysis, followed by clustering methods, and the third most required skill is visualization. So if the data scientist learns these analytical skills and focuses on how to use them it will be of great value to both the data scientist, the companies/ organizations as well as the customers.
Stop Installing Tensorflow using pip for performance sake!
Stop installing Tensorflow using pip! Use conda instead. If you don’t know what conda is, it’s an open source package and environment management system that runs cross-platform. So it works on Mac, Windows, and Linux. If you aren’t already using conda, I recommend that you start as it makes managing your data science tools much more enjoyable.
Review: FCN (Semantic Segmentation)
In this story, Fully Convolutional Network (FCN) for Semantic Segmentation is briefly reviewed. Compared with classification and detection tasks, segmentation is a much more difficult task.
Building a Recommendation System Using Neural Network Embeddings
Deep learning can do some incredible things, but often the uses are obscured in academic papers or require computing resources available only to large corporations. Nonetheless, there are applications of deep learning that can be done on a personal computer with no advanced degree required. In this article, we will see how to use neural network embeddings to create a book recommendation system using all Wikipedia articles on books.
Build the story around data using Exploratory data analysis and pandas.
Build the story around data using Exploratory data analysis and pandas. The art part of data science.
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