Machine learning isn’t a set-it-and-forget-it operation. Even with solid examples, ML algorithms can still fail and end up blocking important emails, filtering out useful content, and causing a variety of other problems. In this O‘Reilly report, industry analyst Ted Cuzzillo examines real-world examples of active learning, a relatively new strategy for improving ML results through short-term human intervention.
Throughout this report, Cuzzillo relies on several experts in the field for practical applications and tips they’ve unearthed through various projects in active learning. As you’ll discover, the point at which algorithms fail is precisely where there’s an opportunity to insert human judgment to actively improve the algorithm’s performance.