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What is the hottest trend in artificial intelligence right now? Machine Learning is the right answer! Thanks to technological advances and emerging frameworks, Machine Learning may soon hit the mainstream. Because of new computing technologies, Machine Learning today is not like Machine Learning of the past. While many Machine Learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data – over and over, faster and faster – is a recent development. Every single day it’s become clear that Machine Learning is already forcing massive changes in the way companies operate. Every Fortune 500 company is already running more efficiently — and making more money — because of Machine Learning. But how this “phenomenon” helps business bring money and attract new and new customers?

Problems that can be easily solved using ML

Every single business some time or other can face with definite problems. But there are some kinds of business problems Machine Learning can prevent if not handle at all:

Email spam filters
Some spam filtering can be done by rules (IE: by overtly blocking IP addresses known explicitly for spam), but much of the filtering is contextual based on the inbox content relevant for each specific user. Lots of email volume and lots of user’s marking “spam” (labeling the data) makes for a good supervised learning problem.

Speech recognition
There is no single combination of sounds to specifically signal human speech, and individual pronunciations differ widely – Machine Learning can identify patterns of speech and help to convert speech to text. Nuance Communications (maker of Dragon Dictation) is among the better known speech recognition companies today.

Face detection
It’s incredibly difficult to write a set of “rules” to allow machines to detect faces (consider all the different skin colors, angles of view, hair / facial hair, etc), but an algorithm can be trained to detect faces, like those used at Facebook. Many tools for facial detection and recognition are open source.

Credit card purchase fraud detection
Like email spam filters, only a small portion of fraud detection can be done using concrete rules. New fraud methods are constantly being used, and systems must adapt to detect these patterns in real time, coaxing out the common signals associated with fraud.

Product / music / movie recommendation
Each person’s preferences are different, and preferences change over time. Companies like Amazon, Netflix and Spotify use ratings and engagement from a huge volume of items (products, songs, etc) to predict what any given user might want to buy, watch, or listen to next.

Here is enumerated not all but just a few problems that can be solved. And with the course of time this list will only expand.

Industries that already use ML in action

Most industries working with large amounts of data have recognized the value of Machine Learning technology. The adoption of Machine Learning is likely to be diverse and across a range of industries, including retail, automotive, financial services, health care, and etc. By gleaning insights from this data – often in real time – organizations are able to work more efficiently or gain an advantage over competitors. In some cases, it will help transform the way companies interact with customers.

Retail industry
Machine Learning could completely reshape the retail customer experience. The improved ability to use facial recognition as a customer identification tool is being applied in new ways by companies such as Amazon at its Amazon Go stores or through its Alexa platform. Amazon Go removes the need for checkouts through the use of computer vision, sensor fusion, and deep or Machine Learning, and it’s expected that many shopping centers and retailers will start to explore similar options this year.

Financial services
Banks and other businesses in the financial industry use Machine Learning technology for two key purposes: to identify important insights in data, and prevent fraud. The insights can identify investment opportunities, or help investors know when to trade. Data mining can also identify clients with high-risk profiles, or use cyber surveillance to pinpoint warning signs of fraud.

Health care
Machine Learning is a fast-growing trend in the health care industry, thanks to the advent of wearable devices and sensors that can use data to assess a patient’s health in real time. The technology can also help medical experts analyze data to identify trends or red flags that may lead to improved diagnoses and treatment. Machine Learning can be used to understand risk factors for disease in large populations. For instance, Medecision company developed an algorithm that is able to identify eight variables to predict avoidable hospitalizations in diabetes patients.

Oil and gas
Finding new energy sources. Analyzing minerals in the ground. Predicting refinery sensor failure. Streamlining oil distribution to make it more efficient and cost-effective, and many others thing that you can do using ML. For example ExxonMobil, the largest publicly traded international oil and gas company, uses technology and innovation to help meet the world’s growing energy needs. Exxon Mobil’s Corporate Strategic Research (CSR) laboratory is a powerhouse in energy research focusing on fundamental science that can lead to technologies having a direct impact on solving our biggest energy challenges.

Government agencies such as public safety and utilities have a particular need for Machine Learning since they have multiple sources of data that can be mined for insights. Analyzing sensor data, for example, identifies ways to increase efficiency and save money. Machine Learning can also help detect fraud and minimize identity theft. Chicago’s Department of Public Health is early adopter. It used to identify children with dangerous levels of lead in their bodies through blood tests and then cleanse their homes of lead paint. Now it tries to spot vulnerable youngsters before they are poisoned.

Marketing and sales
Websites recommending items you might like based on previous purchases are using Machine Learning to analyze your buying history – and promote other items you’d be interested in. This ability to capture data, analyze it and use it to personalize a shopping experience (or implement a marketing campaign) is the future of retail. PayPal, for example, is using Machine Learning to fight money laundering. The company has tools that compare millions of transactions and can precisely distinguish between legitimate and fraudulent transactions between buyers and sellers.

Analyzing data to identify patterns and trends is key to the transportation industry, which relies on making routes more efficient and predicting potential problems to increase profitability. The data analysis and modeling aspects of Machine Learning are important tools to delivery companies, public transportation and other transportation organizations. In some cases, mathematical models are used to optimize shipping routes. By honing in on excessive driving routes, drivers can see a reduction of nearly one mile of driving every day. For a company like UPS, a reduction of one mile per day per driver would equal a savings of as much as $50 million a year in fuel.

Have you ever worked with ML? Was it useful for your business? Or maybe you are still thinking about whether it costs to implement Machine Learning in your business? Will it be relevant and defensibly? If you have an answer on at least one question – share with me your experience. We will be happy to discuss it in comments. But if you don’t have an answer, always remember – Big companies are investing in Machine Learning not because it’s a fad or because it makes them seem cutting edge. They invest because they’ve seen positive ROI. And that’s why innovation will continue.


Yuliya Poshva

Business Development Manager

Skype: juliaposhva
LI Profile: Yuliya Poshva



Altabel Group

Professional Software Development


At all the times healthcare stands as one of the most challenging and pressing sectors of our society. Passed through centuries, wars, incurable diseases, and natural catastrophes, limit of food and water – all these things make us more perceptive to value our life more and give us everyday pressure to think how to improve health sector: to raise the level of our medical knowledge/education, implement innovative materials and technologies, invest in research programs and funds to save one’s life.

Since we have travelled a long way in healing knowledge from experiments and treating with herbs to highly effective medicine till now we continue to search for new methodologies to make the medicine more progressive and effective, to improve patience safety and satisfaction.

Technological and social changes taking place in recent years are affecting the way of presenting and transferring medical knowledge. In the era of IT and high capacity of computers new paradigm has entered in education process- e-learning and its impact becomes more visible and important in the field of medicine.

Nowadays it is hard to imagine healthcare sector without modern information and communication technologies (ICT). Presently, many medical universities and institutions utilize e-learning to make the continuing education process more effective and easy. So, let’s see what the key of E-learning is and what e-learning methods are used in medical education.

E-learning or also called web-based learning, online learning refers to the use of interactive technologies to support and improve teaching and learning process. Historically there were two common e-learning types: distance learning and computer based learning. The first one was used to deliver information to remote locations and the second one uses computers to deliver information. The integrating element of both modes became Internet that implicated multimedia (was one of preceding components before birth of Internet).

E-learning broadly includes different forms/types of delivery of education and teaching components/material to those who connected with this sector on professional or personal level. The delivery of information could be synchronous or asynchronous. It includes a range of technologies from CD-ROM to electronic whiteboards or online simulations. Among popular ones could be mentioned virtual classrooms, audio and video conferencing, digital learning of subjects through digital lectures, digital libraries, animation, textual notes, web based learning platforms, portals, Internet chat forums etc.

Traditionally medical education considers combination of didactic instruction in the classroom with further learning in clinical setting. Later was increased the impact of problem –based learning discussions in order to integrate the science knowledge and clinical decision. E-learning the methods and tools added many dimensions to the educational process and helps to overcome some problems/gaps with traditional education:

–          Flexible learning: remote access to digital materials that are unavailable locally, internet access to the didactic material to lectures and other material.

–          Possibility of collaboration: it helps teachers and students from different universities, countries, which allow exchange of knowledge and experiences;

–          Multimedia helps to transmit training/education video, medical research animation, and simulations of scientific systems;

–          2-D and 3-D computer animation helps in research and educational aims. They help to demonstrate surgery, human anatomy, and more;

–          Instant access to Internet help to stay up-to-date with medical knowledge and achievements;

–          Reduces travel costs and time;

Thank to grow of Internet and educational technologies the number of e-learning resources available to educators extremely increased. Within medical education established repositories and digital libraries provides access to e-learning materials. There are also multimedia online resources that collect links to online learning materials, along with annotations such as users’ reviews and assignments. In addition there is tendency to implement in educational system online learning management systems that help to track and monitor learners’ knowledge, attitude and skills.

Let’s see what are E-learning programs are used to educate patients (customers) and specialists with the use of IT and Internet. They could be of general assignment or specialized ones. For example there are online resources that help patients to understand their disease process, how to prevent infections, it also helps to get information about different medicine products, or get online consultation from doctors on specialized medicine portals care and therapy programs and nursing ones for future mums and babies, training programs. At professional level simulation software helps doctors to prepare for difficult operations virtually; software for medical image interpretation helps to diagnose diseases and prescribe treatment etc. Besides, with the help of video conferencing software systems doctors can share experience and knowledge and being connected/closer to long-distance, disabled or elderly patients. With the popularity of mobile devices the development of mobile tracking applications that traces human activity, sport applications with training exercises and right nutrition allows to take right health decisions and follow balanced healthy life. Promotional video inspires healthy eating; environmental awareness and fitness as a way of life raise the level of wellness and healthcare beyond kids and adults.

Applying new approaches in healthcare sector may empower people to take greater control of their health by supporting healthy lifestyle, improving health decisions. Better Delivery of information also improves emergency preparedness, quality and efficiency of care. As the result it should be said that e-learning is the most effective tool in case of epidemic break-out or any national emergencies it is the most practical and fastest method of passing information to educate the public.

As the result of our small research we may come to the conclusion that healthcare sector is a fast-growing and its integration with IT brings numerous benefits. The knowledge integrated with advanced information and communications infrastructures call changes in all structural spheres, including healthcare. Besides improvements of medical equipment and solutions it brings possibility to develop social connections and helps to solve environmental problems by changing health habits and decisions (when people begin to think over what products they eat and in what environment they leave their attitude of treating the world changes). It modernizes traditional educational/learning systems of different countries and universities, at different educational levels especially of those where people are geographically dispersed to transmit knowledge, skills and learning/teaching styles. E-learning cultivates culture of innovation and productivity in our lives. And how do you think e-learning could benefit in healthcare?

Thank you for your attention and hope to be useful! 🙂


Katerina Bulavskaya

Business Development Manager



Altabel Group

Professional Software Development


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