Machine learning is the science of getting computers to act without being explicitly programmed. Using an experimental interactive design, the new R2D3 Blog offers an instructive Visual Introduction to Machine Learning.
Summary
- Machine learning identifies patterns using statistical learning and computers by unearthing boundaries in data sets. You can use it to make predictions.
- One method for making predictions is called a decision trees, which uses a series of if-then statements to identify boundaries and define patterns in the data.
- Overfitting happens when some boundaries are based on on distinctions that don’t make a difference. You can see if a model overfits by having test data flow through the model.
In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.
How pervasive is machine learning today?
In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI.
