The book Human-in-the Loop Machine Learning by Randall Munro has a code example of finding hazards in food safety reports. Here's the description of the problem: Food Safety professionals want to collect data from incident reports about where pathogens or foreign objects have been detected in food. “I want to maintain a complete record of all recorded food safety incidents in the EU” “I want to track when different food safety incidents might have come from the same source” “I want to send warnings to specific countries when there are likely to be food safety incidents that have not yet been detected or reported” The interface has fields for "Hazard", "Food", "Origin", and "Destination" along with a short extract of text from a food report.
The book Human-in-the Loop Machine Learning by Randall Munro has a code example of annotating bicycles. Here's the description of the problem: Transportation researchers want to estimate the number of people who use bicycles on certain streets. “I want to collect information about how often people are cycling down a street” “I want to capture this information from thousands of cameras and I don’t have the budget to do this manually” “I want my model to be as accurate as possible” Based on this he has designed an interface for rapid annotation.
The book Human-in-the Loop Machine Learning by Randall Munro has a code example of annotating headlines for a data analyst. First you choose a topic name and then can annotate examples. For example I chose "sports results" intending to label headlines containing the result of a sport contest (and not other kinds, e.g. political contests). It wasn't totally obvious how to annotate examples at first; I had to click in the box with the example headline.
Most machine learning models are guided by human examples, but most machine learning texts and courses focus only on the algorithms. You can often get state-of-the-art results with good data and simple algorithms, but you rarely get state-of-the-art results with the best algorithm build on bad data. Robert (Munro) Monarch, Human-in-the Loop Machine Learning Human-in-the Loop Machine Learning by Robert (Munro) Monarch is an excellent book on annotating data for Deep Learning practitioners in industry.
The Gulag Archipelago is a singular piece of literature about the horrors of arbitrary arrest, inhumane interrogations, prolonged imprisonments, deadly work camps and exile that impacted tens of millions of people in the first half of the twentieth century. Aleksandr Solzhenitsyn has a way of conveying these horrors in a truly compelling way; somehow the descriptions of torture are close and detailed enough to be vivid, varied enough to be somewhat comprehensive, yet not repetitive nor gratuitous.
Johnathan Haidt's The Righeous Mind: Why Good People are Divided by Politics and Religion is about the moral norms of groups. As someone not familiar with moral psychology I found the book discussed many interesting ideas I wasn't aware of, but didn't provide much evidence for Haidt's own theories and claims. The book is reasonably well written with good structure and some excellent metaphors, but sometimes goes on unnecessarily long detours into the author's personal life and the repetition can be wearing.
Michael Lewis' The Fifth Risk promotes parts of the US public service and some people who work in it. The public service is culturally opposed, if not legally prevented, from promoting itself which means a lot of the successes and heros go unsung. Michael Lewis spells out what some of the largest, yet most obscure parts, of the US government accomplish and how they could be at risk through mismanagement of the Trump administration.
Edward Chancellor's Devil Take the Hindmost: A History of Financial Speculation is a history of several market bubbles and crashes. It covers bubbles such as the South Sea Bubble, the 1920s bubble in the US stock market preceding the great depression, the dotcom bubble of the 1990's and Japan in the 1980's. The main lessons I took was if a market sounds too good to be true it probably is, that highly leveraged financial instruments tend to prolong and worsen bubbles and often the people who bear the cost of reckless speculation are different to the people who take and profit from it.