Tools and Techniques
This is a continuation of DataCamp's comprehensive tutorial for importing data into R. It's easy to follow and covers a wide variety of file types. In addition to a number of file types that weren't covered in Part 1, this part includes a section that specifically addresses large datasets.
Easy to follow introduction to eigenvectors and their relationship to matrices. For the most part, this is a plain English tutorial that continues with covariance, principal component analysis, and information entropy.
Practical guide to help software developers get started with machine learning.
IDEO is well-known for its human-centered approach to design. Here's an important read about how that relates to data.