Recognize cases when machine learning can help in investigations, use tools to tackle real-world reporting issues, and better understand how AI is used by your sources.
Sifting through terabytes of documents or images might take years — unless you teach a computer to do it for you. Like a bloodhound, a machine-learning algorithm can take a "sniff" or sample, of what you're looking for and find "more like this."In this class, students will learn to recognize cases when machine learning might help solve such reporting problems, to use existing and custom-made tools to tackle real-world issues, and better understand AI principles and pitfalls in general.
Take this class if you are a data journalist or anyone looking to learn more about the practical journalistic applications of artificial intelligence.
General principles behind machine learning, explained in ways tailored for journalists
Coding "notebooks" and open-source machine learning libraries
Hands-on experience using machine learning to classify images.
A hands-on introduction to using machine learning for text documents.
Real-world examples of how machine learning has helped journalists, including some unexpected examples of how image-detection can be helpful.
This webinar was recorded on May 5 and 12, 2020. Closed Captioning available for this video.
Level: Beginner to Intermediate