From Deep Learning for Vision Systems by Mohamed Elgendy
In this part, we will take a look at feature extraction—a core component of the computer vision pipeline.
From Graph Databases in Action by Dave Bechberger and Josh Perryman
In this article, we’ll review what makes a problem a good graph use case. We’ll start by examining a few general categories of problems and discussing why they might make for good graph use case. Finally, we’ll analyze a general framework that we can use to help us decide if our problem is a good graph use case.
From Mastering Large Datasets by JT Wolohan
This article explores using the map function creatively in a data project.
From Machine Learning with R, tidyverse, and mlr by Hefin Rhys
This article covers:
• What the tidyverse is
• What’s meant by tidy data
• How to install and load the tidyverse
• How to use the tibble, dplyr, ggplot2 and tidyr packages of the tidyverse