Machine Learning
Explore the fundamental concepts of machine learning, including supervised, unsupervised, reinforcement, and deep learning methods. Understand how data quality influences model success and learn to differentiate machine learning from broader AI terms in product contexts.
ML concepts and specialization
ML is a general concept that gives us the basic thinking and organizing power that gives machines the ability to reason with data in a way a human might. We can think of this as a way for a machine to mimic how a human can think, understand, and work. It dominates the market, and it serves as its own umbrella term of sorts because, within it, we can break down ML into the models we associate with traditional ML, along with their specializations, such as computer vision, NLP, and DL, as further subsets of ML.
Recap of ML models and learning types
To jog our memory, those learning types are supervised learning, unsupervised learning, reinforcement learning, and deep learning (neural networks). All these ...
