Machine learning, in simple words, is the learning of the computer on its own as its experiences ascend. The way the efficiency of humans increases with experience in a particular field, machines might also be capable of it. Machine learning is a human-like behavior that the machines or computers show by mastering on it without us needing to further code. There are tons of different ways that can define machine learning. But, if you have no idea about machine learning then, this is the easiest way you can understand it.
Machine learning is based on algorithms and machines use these algorithms to upgrade their experience with time without needing to be explicitly programmed. Machines develop or improve their process of learning by finding the pattern for doing certain things. They play around with the statistics and examples that we provide so that they can make better decisions in the future. This is a way for machines to become more independent.
People often get confused with Machine Learning and Artificial Intelligence.
Artificial Intelligence is the advancement of computer systems to perform tasks that normally require human knowledge. Artificial Intelligence is a very broad topic that covers a vast range of knowledge regarding the learning of new things by computerized systems.
Machine learning and deep learning are simply the branches or subdivisions of Artificial Intelligence. Thus, artificial intelligence and machine learning are not the same. Everything that artificial Intelligence covers are not machine learning but in contrast, everything included in machine learning is a part of AI.
Artificial Intelligence is a technology that encourages machines to adapt human intelligence or human behavior while machine learning is a part of the artificial intelligence that enables machines to learn on their own.
The main purpose of Machine Learning is to discover new methods or ways to provide the most accurate results while Artificial Intelligence is to enhance the problem-solving skills of computers and machines.
Machine learning is a limited scope while Artificial Intelligence is a wide scope that covers a lot more than a Machine Learning does.
Machine learning can be further divided into three main types, Supervised Learning, Unsupervised Learning, and Reinforcement Learning while AI has further Weak AI, General AI, and Strong AI.
This is a great question because just knowing about what is machine learning is not enough. You must know the applications of machine learning to fully understand it.
Machine learning has been a very well-known subject of this 21st century and it is slowing marching towards capturing the whole world. Let's find out what machine learning is all about and what is machine learning used for.
Data security is very crucial for preserving personal and official information within a specific organization or company. There has been a lot of malware out there like viruses, horses, worms, Trojans, etc. The only intention with which these Malwares have been created is to damage any computerized system to have access to its personal data and information. Machine learning is an expert in finding such malware. As most of the malware has similar properties with very few differences of around 6-10%, machine learning plays a key role in detecting them. The algorithms used in Machine Learning search for similar patterns of malware and thus provide security against vandalism.
Personal security doesn't just mean your own personal security. In fact, it also means the security of a certain place or even a specific country. While traveling from one country to another or even from a place to another, you are required for security screenings. These machines use Machine Learning techniques to identify all the suspicious things that you might have in your baggage and even on your body.
Machine Learning, nowadays, has been used in almost every aspect of the medical field. For example, machine learning is used in the early processes of drug manufacturing. Machine Learning helps in identifying the patterns of the data without any guidance. Machine learning also helps in recognizing cancer in most of the patients and it is also widely used in the treatment processes of cancer. Besides these, there are plenty of other applications of Machine Learning in Healthcare like Smart health records, clinical trials, and research.
Machine learning is the most widely used in digital marketing. You for sure have noticed that searching certain things on google and not buying it will cause the advertisement of the same thing to pop up in social media like Facebook, Instagram, and even on other websites that you visit. The marketing world runs with the same motive, the more you know about your customers, the better you can assist them in achieving their goal as well as your own goal.
It is surprisingly interesting to see how machine learning has left its footprint in almost all the industries. Machine learning has been used in almost all fields like Healthcare, Marketing, Financing, Security, etc. In addition, in the past couple of years, Machine Learning has also been widely used by Petroleum Engineers in the oil and gas industries.
The main purpose of using Machine Learning techniques, almost everywhere, is to decrease the workload. As laziness and lazy people oftentimes lead to new inventions, Machine Learning was introduced to help people perform their tasks easily.
Machine Learning is truly something that helps reduce the workload incredibly. In the field that uses Machine Learning, the burden of the work is reduced to a great extent. It decreases the work burden to a great extent and thus saves a lot of time and money. When machines can perform the same task in an easier and faster way, employers can save a huge sum of money that they pay to their employees as their salary.
Wait, at this point, you should have an important question on your mind.
The brief and straightforward answer is no. If the use of Machine Learning and Artificial Intelligence keeps on increasing the way they are now then, this can put the whole world in extreme danger. Think of it, using Machine Learning techniques, machines can learn new things that are not taught to them. Now, imagine how dangerous that could be to humans. This might lead the world to the next dangerous era of human eating.
Supervised learning can be understood as an algorithm method of Machine Learning that helps in providing future predictions. It involves the learning of the machine from the past data and patterns to analyze any unforeseen data in the future. We provide computers with the data and examples on how to analyze those data. From using the provided example and playing around with the data on its own, computers come up with a pattern to predict future data.
Unlike Supervised Learning, the Unsupervised Learning algorithm method of Machine Learning is the way computers learn on their own without any guidance or examples. In Unsupervised Learning, computers might be teaching human beings on how to analyze. This is very useful in some cases when humans can determine how to begin analyzing the given data. This method of Machine learning is most widely used in pattern recognition and descriptive modeling.
In the previously discussed algorithm methods of Machine Learning, we either provided labels to the computer, or no label was provided at all for the observation. But, this method of Machine Learning doesn't resemble any of these two methods but instead, lies in between them. In this method, the labels are not provided most of the time and are only provided seldom. This type of Machine Learning Algorithm is most widely used in building models.
Among all the different algorithm methods of Machine Learning, Reinforcement Learning is a very wide topic and it is also a branch of Artificial Intelligence. The Reinforcement Learning Algorithm is oftentimes also called an agent. It iteratively learns from its experience to fully recognize all the different patterns that are possible.
At last, but not least, let's have a touch of Deep Learning and how it works.
Deep learning is the part of Artificial Intelligence and it is also a sub-division of Machine Learning. It copies the processing pattern of the human brain in interpreting data, identifying objects, translation of the languages, and taking the most profitable decisions. Deep learning Artificial Intelligence is fast forward and it can easily learn, analyze, and interpret the unstructured and unlabeled data.
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