The amount of data that’s collected and stored is staggering, and it’s always growing. This constant growth means, constant change. More companies are doing business online and must adapt to the growing security risks that go along with this cyber age. This has caused a boom for the IT industry as every business today seems to rely on some level of IT support. Enter machine learning.
Machine language is a form of artificial intelligence that aids computers with the ability to learn without being visibly programed. It focuses on the development of computer programs that can be able to teach themselves how to change when exposed to new data. Machine learning programs can detect patterns in data, and adjust the program action accordingly.
Machine learning service basically does three different tasks:
- Predict outcome (for example, yes or no)
- Predict multiple conditions like detecting customer web shopping behaviours.
- Yielding an actual value, such as predicting the right price or the number of units that will sell.
Below are the benefits of machine learning techniques:
Machine learning helps to detect fraud, and prevent it from happening. It is done by use of customer information such as spending details, membership card details, and merchant information. This data helps in ensuring normal business transactions continue, and still detect and stop fraudulent transactions before they happen. A good fraud detection system should be able to detect suspicious activities and stop them in a few milliseconds.
Attracting and retaining new customers
All businesses aim to attract more customers and also retain the existing ones. To achieve this, you have to provide the most persuasive user experience possible. To have a competitive advantage, there is the need for a tailored user experience. The price and the target market has to be right. To attain this, there is the need for machine learning techniques, which accumulates data that can improve and evolve with the market trends and the customers’ needs. Such capabilities help a business maintain its customers and attract more since you are able to detect their need and conform to them at the right time.
Clustering and categorization
Machine learning techniques at many times involve clustering and categorization. There is a lot of data in business that, if not well arranged, can be difficult to find when one needs to use them. However, with machine learning, like objects are placed together effectively, thus retrieving them becomes easy. This works in a way that the machine that groups customers can also be used for advertising and one that groups email will also help in identifying spams.
There is a lot of large-scale data today to work within many IT departments. When an anomaly occurs it can be very difficult to identify the problem, it is also time-consuming. IT becomes a lot harder when there is a special event and many people are using the same system at the same time. With machine learning, however, it becomes easier to detect instantly any anomalies and direct more resources to the section to avoid overloading the system.
Machine learning has the capability to do repeatable tasks. When working with data at the scale of terabytes, version control can be very expensive. Making full copies of all this data can be very costly, however, machine learning allows for consistent snapshots that helps one to reference data, compare new and old data, and ultimately see what causes the changes.
Machine learning programs use experience to modify algorithms. Once you have identified anything in your system, there will be no need to keep repeating the same procedure every time. It can remember, and do the same procedure for you in future. Mail programs such as Gmail gives the user the option to identify spam mail, after you have identified it, it is filtered and is categorized as spam. Thus, Gmail is able to filter more spam mail that have been previously identified.
Undoubtedly, machine learning is a reasonably implausible tool. Computers have gone to the realms where at one time was considered to be a human domain. The technology of machine learning at the moment is still being developed, and its concept keeps on improving continuously. In the near future, it promises to help us with most of our problems, as well as create more opportunities.