Knowledge Quadrant for Machine Learning

Most Machine Learning systems that are deployed in the world today learn from human feedback. For example, a self-driving car can understand a stop sign because humans have manually labeled 1,000s of examples of stop signs in videos taken from cars. Those labeled examples are what teaches the algorithms deployed in the cars to automatically identify the stop signs. However, most Machine Learning courses focus almost exclusively on the algorithms, not the Human-Computer Interaction part of the systems. This can leave a big knowledge gap for Data Scientists working in real-world Machine Learning, where they will spend more time on data management than on building algorithms.