Understanding the application of ML
Today, ML is widely used in every industry to help companies and non-profit organizations gain deeper insights into their business through data. As a branch of artificial intelligence, it allows you to apply statistics with historical data to predict outcomes, forecast future values, detect anomalies in patterns, and more.
Some of the most popular techniques or algorithms used in ML are listed as follows:
- Regression: This helps you respond to questions such as how much or how many. For example, how many units will I sell next quarter? How much crime will a region have next month? What is the projected fuel consumption given certain variables?
- Classification: This helps you categorize events or data points. For example, will this customer churn (yes or no)? What animal is this?
- Clustering: This helps you group data points together. For example, which customers tend to purchase this product? Which demographics are likely to engage...