Tools and Techniques
This step-by-step guide for extracting information from text data is one of the best you'll find. It's very well written and it includes an interactive notebook, helpful graphics, and lots of links to other resources.
Kaylin Pavlik collected text reviews for 30,000+ beers and then analyzed them using R and tidytext. This is a fantastic writeup of her approach, including code, visualizations, and her discoveries along the way.
This latest article from Google's People + AI Research Group (PAIR) explores how finding ways to augment human capabilities, rather than just making machines "smarter," actually unlocks greater potential in the machines. If you're interested in human-computer collaboration, the entire series is great.
This roundup of top R packages that Joseph Rickert puts together is definitely worth spending some time with. This latest issue includes packages for a variety of uses, including computational methods, machine learning, visualizations, and statistics.
Here's a pure Python implementation of a neural-network based Go AI, using TensorFlow. It's not the official DeepMind project but it strives to replicate the results of the AlphaGo Zero paper from Nature and it looks like a great project to learn from.
Get this whitepaper and learn how ITSM must evolve to bridge the gap between ITSM and DevOps.