Machine Learning (ML) provides Artificial Intelligence machines the ability to “learn.” This is achieved by using algorithms that discover patterns and generate insights from data.
Unlike traditional programming, you’re not giving the computer detailed instructions on what to do. Instead, you give the computer data and tools that allow it to study and solve the problem without directive. The computer remembers and adapts to new information each time it is used, also known as learning.
Use ML when you can’t tell the computer explicitly what to do in each situation.
Types of Machine Learning
- Supervised – You show the machine connection between variables and outcomes. It’s like a knowledgeable tutor.
- Unsupervised – The machine learns through lots of observation and trial and error. Unlike supervised learning, you’re not showing the machine the correct answer. The more data you give it, the more accurate the machine will become.
- Semi-supervised – Mix between supervised and unsupervised.
- Reinforcement – The machine gets a reward for performing a desired action.
Joshua Bowen's Notes 