Machine learning is the process of a computer system’s performance being improved by being programmed to act based on previous experience. This is very different from how traditional, rule-based computer programming works.
We’ve compiled 10 reasons you should study machine learning and join the world of tomorrow’s workforce!
Machine Learning is a new and exciting branch of Artificial Intelligence. It has been called one of the “biggest information technology breakthroughs in decades” and the “next big thing” because it could create significant changes in every industry by replacing human decision-making with automation.
Machine Learning consists of an artificial intelligence component programmed to act based on previous experience, which can take many forms from pattern recognition to statistical modeling.
The capabilities of Machine Learning have made it one of the key domains within AI research for building intelligent computer systems that can augment human intelligence.
A machine learning project typically starts with a mathematical model based on an analysis of past data, which can be classified into records and groups known as clusters or features.
Then, the model is trained on the data by using a statistical learning algorithm. The training leads to improved performance (i.e., a better output prediction). Afterward, the trained model can be used in predictive analytics to predict future results based on historical information that was not part of the original dataset. A great resource to start with is programminggeeks.
These algorithms are classified into three broad categories: supervised, unsupervised, and reinforcement learning.
The old way to do things was through rule-based programming; in other words, programmers told a computer what to do.
But with machine learning, computers need much less hand-holding. Machine learning does the work for you! So its key benefit is that after software programs are trained with data sets, they can answer certain types of questions more efficiently than humans and become experts themselves, and make smarter decisions about how to train themselves.
Example: When learning the basics of machine learning, you can be taught how to program a computer system capable of making its own learning-based decisions and then improve itself through those same processes. And if you add artificial intelligence into this equation, it allows machines to better predict what complicated patterns mean based on previous experience.
The long answer as to who should study it is complicated; it depends on many factors. But let’s take a look at some reasons why a student would benefit from studying machine learning:
- You’re interested in math-based problem solving, emphasizing statistics and data analysis because machine learning uses inference algorithms derived from probability theory and statistics (it also uses optimization techniques).
- You have a natural curiosity about how the human brain works so that you can learn how to program machines that are capable of abstract thinking and learning using artificial neural networks (if you’re not familiar with artificial neural networks, they’re self-learning computer programs modeled after biological nervous systems in animals).
- You want to become involved in solving big problems involving very large, complex data sets such as drug discovery, medical records analysis, or even livestock animal cloning because these types of work benefit from machine learning’s capabilities of deep pattern recognition and expert decision making based on previously learned knowledge.
- You like working with big data or large amounts of information because this field deals with analyzing huge amounts of information that humans would never be able to process in a reasonable amount of time.
- You want to create virtual agents, such as chatbots or avatar robots, capable of intelligent conversation with human beings using natural language processing algorithms and machine learning techniques.
- You have a knack for computer science and enjoy creating new technology so that you can help build the infrastructure for future technologies such as self-driving cars, drones, and robots that can perform many tasks.
- You want to be involved in finding solutions to business problems using predictive analytics so that you can help businesses understand their customers’ needs and therefore create better products or services.
- Your mission is to improve computer systems based on statistical algorithms such as computer vision systems, speech recognition systems, and natural language processing systems to solve problems like online fraud detection.
- You want to help with the analysis of large-scale datasets using advanced statistical methods so that you can analyze medical studies or crime patterns cost-effectively (by reducing human error).
- You believe artificial intelligence awareness will become widespread in the future, and so you want to help advance this technology before it arrives on our doorsteps
With all of these benefits, studying machine learning is worth considering. So what are you waiting for? See if your university offers a course and begin applying some math-based problem-solving skills to real-world problems!