What Is Machine Learning?
Machine learning is an area of artificial intelligence where systems can learn and improve from experience without being explicitly programmed to do so. Machine learning is a subset of artificial intelligence that deals with the development of algorithms that can learn from and make predictions on data.
Machine learning is a process of making computers more human-like by teaching them to make decisions for themselves. This knowledge includes anything that can be readily written or recorded, such as textbooks, videos, or manuals. With machine learning, computers are now gaining tacit knowledge—that is, the kind of knowledge we gain from personal experience and context. This type of knowledge is difficult to transfer from one individual to another through written or verbal means.
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 and 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.
Machine learning is a field of computer science that deals with the design and development of algorithms that allow computers to learn from data, identify patterns and make predictions. The utilization of tacit knowledge by machine learning has resulted in the technology being sought after by nearly every industry, from fintech to weather and government.
Deep Learning
Deep learning is a subfield of machine learning that is concerned with the extraction of higher level features from raw data using Artificial Neural Networks (ANNs). Artificial Neural Networks (ANNs) are much different from human brains, but they were inspired by the way humans process information. The learning a computer does is considered “deep” because the networks use layering to learn from, and interpret, raw information.
Google is using deep learning to discover patterns in images and display the most relevant image for a given search. If you search for a winter jacket, Google's machine learning algorithms will analyze images to discover patterns (sizes, colors, shapes, relevant brand titles, etc.) that display pertinent jackets that satisfy your query. Deep learning is also making advances in radiology, pathology, and any medical sector that relies heavily on imagery. The technology relies on its vast knowledge (from studying millions of other scans) to immediately identify diseases or injuries, saving time and money for both doctors and hospitals.
