Modern Machine Learning applications

by Admin iOnhax
Modern Machine Learning applications - Modern Machine Learning applications
Modern Machine Learning applications

Today, machine learning is one of the most popular areas of AI. Thanks to the widespread use of various digital devices, machine learning is being talked about as a revolutionary way to solve various tasks, including text and image recognition, data classification and analysis, forecasting, and other functions.

When the largest companies (Google, Amazon, Apple, and others) started using machine learning algorithms in their projects, other companies quickly reacted to the new trend.

 There is a great demand for the development of software applications with an AI component: from fitness simulators to various image recognition systems (road signs, license plates, etc.). These applications not only find their audience but also attract more and more attention. They are based on special algorithms that offer unique features to all users of the application.

Features of applications that have a machine learning algorithm

Today, many processes already use AI algorithms, but ordinary people do not even think about how far machine learning has already gone.

– Customization

Most of the clients of various companies seek to receive personal service and approach. Companies, in turn, strive for personalized communication, but hiring employees for each client is mostly unprofitable.

Customized applications allow you to customize them exclusively for all the wishes of any client, while employees do not participate in this process, all the work is done directly by the application. Collecting all information about the user (requests, preferences, personal and other information). These applications will appear in many companies in the future, as they improve the quality of service, while they do not require additional costs (only at the initial stage). This technique is already used in targeted advertising and social networks (which is why the user sees ads for products that he has recently been interested in).

– Recognition of various content

The most popular and famous example is the Face ID function, which is used on iPhones and iPad. Applications have also been developed that show how a person will look in a few years or even decades.

However, these algorithms are used not only for entertainment purposes. This method is actively used in various security systems at security facilities, while additional parameters can be used (retina, palm or fingerprint, and others). Previously, this could only be seen in films, but perhaps soon it will be found everywhere.

– Text Recognition

This function is necessary for many people, as it saves a lot of time and at the same time allows you to read texts in various languages. Currently, a large number of different fonts are used in texts, which have different features, which will complicate the machine learning process. That is why different types of models are used to perform these tasks, which are created taking into account various features of languages and the scope of their use.

Unfortunately, there is no single application (program) that would equally well cope with all the necessary tasks, but recent models have begun to appear that can perform several functions at once. This fact indicates that progress does not stand still, an application should soon appear that should eliminate all existing language barriers.

– Sound recognition

Almost anyone who has used a modern smartphone has already encountered such applications. Such algorithms are included in Siri and Google. Of course, they do not always work perfectly, however, from the moment of release (their direct implementation) they have made significant progress and improved.

– Analysis of sensor data

There are already many different applications that use machine learning in their work. Various sports applications, health analysis, and sleep analysis applications help many users to monitor various parameters, but they all require an initial set of different data (weight, age, height, etc.).

Learning algorithms make it possible to significantly improve the efficiency of these applications, while the application user does not need to continue to enter new data into it. From the point of view of the end-user, this feature provides additional advantages and convenience.

Some applications are used to monitor the health of patients and prevent critical situations. They track various indicators and process the information obtained using a machine learning model. When an attack occurs (the risk of an attack), the application “signals” about it by sending a message to loved ones (or institutions) who can come to the rescue.

– Navigation and control of actions

Such applications can also be significantly improved with the help of machine learning. When integrating these applications with other servers, they will be able to analyze various situations. For example, in case of danger, they will be able to warn the driver about it, recognize traffic jams, dangerous drivers, and other traffic characteristics.

– Forecasting trends based on analysis

With the help of Big Data, it is possible to solve many different tasks for various forecasting based on information based on archival data and various statistics. Such services are already used by the world’s largest companies (Amazon Mobile Analytics or Google Cloud Machine Learning).

Data analysis will help to improve the application, as well as help to understand what exactly is interesting to most users. You can also get more information about the end-user and create an image of him, which will allow you to offer him the most relevant offers and services that may interest him.

Development prospects

According to the forecasts of many scientists and reputable publications, machine learning will significantly strengthen its position in the development of various kinds of software, and this industry should become one of the leading industries of the future. It is of interest to large and small businesses, ordinary people, and entire states.

This is since these algorithms can perform various tasks that in the future should help not only improve certain applications but also make people’s lives easier in general. They will be actively used not only by large companies but also by ordinary people.

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