How Machine Learning Works
Machine learning is the core driver of AI. It’s the process of using algorithms to tell you something interesting about your data without writing code specific to the problem you’re trying to solve. Said differently, it’s a way to have computers learn from data with minimal programming. Instead of writing code, you feed a machine data and it builds its own logical function based on this data. Here is a brief overview of a few of the most important components of AI.
- Natural language understanding (NLU) refers to systems that handle communication between people and machines.
- Natural language processing (NLP) is distinct from NLU and describes a machine’s ability to understand what humans mean when they speak as they naturally would to another human.
- Named entity recognition (NER) labels sequences of words and picks out the important things like names, dates, and times. NER involves breaking apart a sentence into segments that a computer can understand and respond to quickly.
- Deep learning refers to artificial neural networks being developed between data points in large databases. Just like our human mind connects the dots to give us insights, deep learning uses algorithms to sift through data, draw conclusions, and enhance performance.