Machine learning is the branch of Artificial Intelligence (AI). In AI, the machines are designed to simulate human behavior. Whereas in machine learning, the machines are allowed to learn from the past data without programming explicitly. Any technology user in today’s world has benefitted from machine learning. It is a continuously growing field and hence provides several opportunities to the research industries. In machine learning, tasks are classified into broad categories. Two of the most adopted machine learning categories are supervised learning and unsupervised learning. In supervised learning, the machines train the algorithms based on the sample input and output labeled by the humans. It uses patterns to predict values on additional unlabeled data. In unsupervised learning, the machine trains the algorithm with no labeled data. It will find the structure within its input data. As a field, machine learning deals with data, so having a piece of knowledge in statistics will be useful in better understanding concepts.
WHY MACHINE LEARNING?
- It develops systems that can automatically adapt and customize themselves according to the individuals.
- It can be a key for unlocking the value of corporate and customer data which in turn helps the company to stay ahead of the competition.
- For growing data and the different available data, the computational process is cheaper and faster and provides affordable storage.
- By using algorithms to build models, organizations can make better decisions without human intervention.
- Relationships and correlations can be hidden in a large amount of data. Machine learning will help find these relationships.
- As technology keeps changing, it is difficult to continuously redesign the system by hand.
- In some cases like medical diagnostics, the amount of data available about certain tasks might be too large for explicitly encoding by humans.
VARIOUS FIELDS THAT USES MACHINE LEARNING:
GOVERNMENT: By using machine learning systems, the prediction of potential future scenarios and adapting rapid changes becomes easy for government officials. Machine learning helps to improve cybersecurity and cyber intelligence. It also helps by reducing the failure rates of the project.
HEALTHCARE: The use of sensors to predict the pulse rate, heartbeats, sugar levels, sleeping patterns helps the doctors to assess their patient’s health in real-time. It provides real-time data from past surgeries and past medical records which will improve the accuracy of the surgical robot tools. Some of the benefits are avoidance of human errors and will be helpful during complex surgeries.
MARKETING AND SALES: The marketing sector has been revolutionized since the arrival of artificial intelligence (AI) and machine learning. It has increased customer satisfaction by 10%. E-commerce and social media sites use machine learning to analyze the things that you are interested in and help in suggesting similar products to you based on your past habits. It has greatly helped in increasing the sales of e-shopping sites.
TRANSPORTATION: Through deep learning, machine learning, has explored the complex interactions of highways, traffic roads, accident-prone areas, crashes, environmental changes, and so on. It helped in traffic control management by providing results from the past day. So, the company can able to get their raw materials without any delay and supply their finished goods to the market inefficient time.
FINANCE: The insights produced by machine learnings helps the investors to give a clear picture of risk and the right time for investment and helps to identify the high-risk clients and signs of fraudulent areas. It helps in analyzing the stock market movement to give financial recommendations. Machine learning also helps to be aware of the risks in the finance department.
MANUFACTURING: Machine learning has helped to improve productivity in the industrial field. It helps in the expansion of product and service lines due to mass production in a short time. Improved quality control with insights helps to improve the product’s quality. Ability to meet the customer’s new needs. Prediction helps to find risks and reduces the cost of production.
Thus in today’s world, machine learning is implemented in several fields to complete the work faster and cheaper. The machine should be able to do all the works that man can do and machine learning will help to achieve this goal.