What Is Machine Learning? Why Does It Matter?

Machine learning is a form of AI-based learning application that does not have a program or guideline that it will follow. Rather it has data, history, charts, and variables, that allow the AI to take decisions after deep learning sessions. With time, the AI can suggest, predict and assist on its own without any human intervention. 

To put it simply, it is a form of a learning algorithm for the AI which gains knowledge on its own. This article will give you a clear concept about machine learning and its uses.

What is Machine Learning

Machine learning is a field of computer science which gives computers the ability to learn without being programmed explicitly. If machine learning is introduced into a system, then the system can learn from data, identify patterns. The system can also make decisions like human and animals. Machine learning algorithms use some computational methods to access information and learn from that information. The algorithms then gradually improve their performance as they find available samples to learn from them.

Some Definitions

1. “Machine learning is the science of getting computers to act without being explicitly programmed.” – Stanford (link- http://online.stanford.edu/course/machine-learning)
2. “Machine learning is based on algorithms that can learn from data without relying on rules-based programming.”- McKinsey & Co. (link- https://www.mckinsey.com/industries/high-tech/our-insights/an-executives-guide-to-machine-learning)
3. Machine learning (ML)is a fascinating field of Artificial Intelligence (AI) research and practice where we investigate how computer agents can improve their perception, cognition, and action with experience. Machine Learning is about machines improving from data, knowledge, experience, and interaction. – Carnegie Mellon University (Link- https://www.ml.cmu.edu/)

Machine Learning History

Arthur Samuel, an American pioneer coined the term “Machine Learning” in 1959. In the early days of AI, some researchers became interested in giving a system the ability to learn from data. Neural network and other terms were then invented with the flow of that interest.

In the early of 1980s, an increasing emphasis on the logical, knowledge-based approach joined Artificial Intelligence and Machine Learning together. After that, “Expert System” came to dominate AI. Researchers used to introduce symbolic/ knowledge-based learning within AI. Soon, pattern recognition and information retrieval were made possible through machine learning and AI. In that time, machine learning was used with AI to solve problems of a practical nature.

In the 1990s, machine learning was separated from AI and was recognized as a separate field. It started working on statistics and probability theory rather than its symbolic approaches inherited from AI.

Machine learning was then joined and separated from many sections and reached in its present condition. But now, an artificially intelligent system is incomplete without machine learning. As science and technology are advancing quickly, machine learning is becoming more important and popular.

How Does Machine Learning work?

Machine learning is a popular word in the technology world. It has given the computers the ability to learn. But how that works? Actually, machine learning is introduced in a system by introducing a set of algorithms. Basically, a teaching set of data is given to a machine learning algorithm. Then the system is asked to answer a question. For example, you want your computer to learn your and your family members’ voices. Then you might provide your computer with your and your family members’ voices. It then started to learn from that data. Then, if you give your computer a series of voices, it will be able to identify which voice is whose.

The machine then started to learn on its own. Suppose, if you give your computer an unknown person’s voice, it doesn’t matter whether it could identify the voice correctly or incorrectly, the voice’s data gets added to the teaching set of data. Thus, the program gets smarter as it faces many problems.

Why Does Machine Learning Matter?

Machine learning has become a key technique for solving problems because of rising in big data. Some examples are given below:

1. Computational Finance: Machine learning is becoming more popular in computational finance. It is used for credit scoring and algorithmic trading.
2. Image Processing: For better and correct output, machine learning is used in image processing. Some artificially intelligent software can create an image by calculating some data.
3. Security: Machine learning is now so much important in terms of security issue. It is used for face recognition and motion detection. Even object can be detected and recognized by machine learning. Without machine learning, these were not possible to impose.
4. Computational Biology: biological computation was made possible by machine learning. Machine learning is used to detect tumor and cancer. It is used to discover drugs. Finding DNA sequence of anything is not possible without machine learning.
5. Natural Language Processing: Voice recognition is important for security purpose. Machine learning is used for voice recognition. If you have used any artificially intelligent voice assistant like Siri or Google Assistant, then you have seen that your voice is taken as input in the software. But how is that possible? Machine learning is used to translate that voice into machine language. Though in Android, the Goggle Assistant can be stopped.
6. Manufacturing: Automated transportation is not that perfect yet. But it is going to be successful. Machine learning is used in that system. Machine learning is also introduced in aerospace, automotive and manufacturing for predictive maintenance.

All the procedures described above require big data uses. Machine learning is used to solve big data problem.

Where Can It Be Used?

Machine learning can be used in many sectors such as:

1. Data security: Malware is a huge and growing problem in the technology world. About 325,000 new malware files are detected every day. But institutional intelligence company “Deep Instinct” says that almost all the new malware files are quite same as the older versions. Machine learning is used to detect malware files and the files that can be attacked by malware.
2. Financial Trading: Many businessmen eagerly want to predict what the stock markets will do on a given day. Machine learning is great in such kind of prediction. Many trading firms use systems that are introduced with machine learning to predict and execute trades at a high speed.
3. Healthcare: Machine learning algorithm is able to process and spot more information than human. Statistics show that machine learning successfully identified many diseases before the disease was diagnosed. A company named “Medecision” created a machine learning algorithm. This algorithm is able to identify eight variables. Thus, it can predict avoidable hospitalization in diabetes patients.
4. Marketing: Online selling business is now so much popular nowadays. If you have seen carefully that when you visit an online shop, your favorite products are automatically shown to you. But how is that possible? Machine learning has made it possible. Machine learning learns your choices from your online search, your sharing posts etcetera.
5. Fraud detection: Machine learning is getting better day by day in this matter. For example, “PayPal” is using machine learning to stop money laundering. Machine learning is used to identify a person and his activities. Thus, a fraud person can be detected.
6. Online searching: In this matter, machine learning is so much improved. When you search on Google or Bing, the search engine shows you your expected websites. The algorithms track your responses. When you again search on that search engine, it will show the results with respect to your previous response.
7. Natural Language Processing (NLP): NLP is used in many exciting software to make it interesting and more useful to many persons. Machine learning algorithms process your voice as inputs and generate human-like voice as outputs.
8. Smart Cars: IBM has recently shown a survey result where 74% executives expected to see smart cars on the road by 2025. Not only IOT (Internet of Things) will be integrated into the cars but also the system will learn about its owner’s choice and environment. The car might adjust the temperature, audio, seat position etcetera automatically based on the owner’s choice.

Machine Learning from Human Through Ai

Machine learning is a field of computer science which gives computers the ability to learn without being programmed explicitly. Machine learning is an important part of the artificial intelligence. What does human do when they face a problem? They try to understand and learn from their experience to solve the problem. They memorize it and when they face the same problem or a problem quite similar to that they can face it perfectly. An artificially intelligent system where machine learning is introduced act like a human.

If you give your system a problem, it processes the data given to it and then tries to solve the problem. Whether it is successful or not, it memorizes the data and then uses that response in case it finds a similar problem. Just like human, right? Machine learning algorithms give a system the ability to act and learn as a human.

Summing Up

Machine learning is a popular word in the technology world. It has given the computers the ability to learn from data given to it. Using machine learning, a system can act as a human. Machine learning is a major part of artificial intelligence. But how it works and why does it matter? If you have gone through this whole article, we hope, you now know a lot about machine learning and its applications.