Description
Machine learning is a very promising subfield of artificial intelligence, where systems have the ability to “learn” through data, statistics and trial and error in order to optimize processes and innovate at quicker rates. Machine learning is giving computers the ability to develop human-like learning capabilities that are allowing them to solve some of the world’s toughest problems, ranging from cancer research to climate change.
How, exactly, is machine learning making computers more human-like? Most computer programs rely on code to tell them what to execute or what information to retain (better known as explicit knowledge). This knowledge contains anything that is easily written or recorded, like textbooks, videos or manuals. With machine learning, computers are now gaining tacit knowledge, or the knowledge we gain from personal experience and context. This type of knowledge is hard to transfer from one person to the next via written or verbal communication.
For example, facial recognition is a type of tacit knowledge. We recognize a person’s face, but it is hard for us to accurately describe how or why we recognize it. We rely on our personal knowledge banks to tacitly connect the dots to immediately recognize a person based on their face. Another example is riding a bike. It’s much easier to show someone how to ride a bike than it is to explain it.
Computers no longer have to rely on billions of lines of code to carry out calculations. Machine learning gives computers the power of tacit knowledge that allows these machines to make connections, discover patterns and make predictions based on what it learned in the past. Machine learning’s use of tacit knowledge has made it a go-to technology for almost every industry from fintech to weather and government.
Who this course is for:
- Beginners in data science
