What is Machine Learning? Definitions from Authority Textbooks
Machine Learning is an interdisciplinary field drawing from various information sciences such as computer science, statistics, mathematics, and engineering. According to Tom Mitchell, the author of Machine Learning, it is “the field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience.” This short definition is the foundation of the developer’s definition that will be developed in this article.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, written by three statisticians, describes learning from data as “the statisticians job is to make sense of it all: to extract important patterns and trends and to understand ‘what the data says.’ We call this learning from data.”
Pattern recognition is another perspective of Machine Learning, with Bishop commenting in his book, Pattern Recognition and Machine Learning, that “pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field…”
Finally, Marsland, in his book Machine Learning: An Algorithmic Perspective, underscores the multidisciplinary nature of Machine Learning and the need to approach it from different perspectives.
Drew Conway’s Venn Diagram shows that Machine Learning is the intersection of Hacking and Math & Statistics. The Danger Zone refers to those who know enough to be dangerous, i.e., they can access and structure data, but they lack the expertise to properly analyze it.
Developers Definition
Now that we’ve seen some authoritative definitions of Machine Learning, let’s work out our own definition as developers.
Here is a possible definition of Machine Learning for developers:
Machine Learning is the study of computer algorithms that can improve automatically through experience and by the use of data.
This definition is similar to the one provided by Tom Mitchell, but focuses on the use of data to improve algorithms.
One-Liner Definition-
Finally, let’s work out a one-liner definition that is easy to remember and share with others:
Machine Learning is teaching computers to learn from data, without being explicitly programmed.
This definition captures the essence of Machine Learning and highlights its ability to learn from data, without relying on explicit programming instructions.
Conclusion –
In this blog post, we’ve explored different authoritative definitions of Machine Learning from textbooks in the field, as well as worked out a developer’s definition and a one-liner definition that is easy to remember.
Machine Learning is a complex and multidisciplinary field, but understanding its fundamental concepts is crucial for anyone interested in the future of technology. With the rise of big data and artificial intelligence, Machine Learning is becoming increasingly important in many fields, from finance to healthcare to transportation.
Whether you’re just starting out in Machine Learning or are a seasoned expert, it’s important to keep learning and exploring new techniques and methods. The field is constantly evolving, and staying up-to-date is key to success.
In summary, Machine Learning is a field that aims to teach computers how to learn from data and automatically improve with experience. It is a multidisciplinary field drawing from computer science, statistics, mathematics, engineering, and other information sciences.
