Innovation and various tools that make our life easier have already allowed humanity to make machine learning development company revolution. Nowadays i “data revolution” driven by machine learning. And as we progress, some of the functions that human employees perform today will change. But they will create different jobs, different business models, and whole new industries.
Machine learning is already around us. It is used in programs installed on our smartphones, in cars and smart homes. And also in the software we use at work to analyze information and make better decisions in less time.
The beauty of machine learning is that its uses are almost endless. It can be applied wherever fast data analysis is critical. And it can be revolutionary where it is important to identify trends or anomalies in large datasets. From clinical trials to safety and regulatory compliance.
Minimizing production downtime
Downtime due to breakdowns, interruptions or lack of raw materials can cost a plant millions of dollars. Machine learning helps prevent them. For this, data is collected from the sensors on the equipment, and then they look at what indicators failures occur. In the future, using this information, you can predict when and why a simple one will happen, how to avoid it.
Creation of a production management system
With the help of sensors and machine learning, you can not only perform narrow tasks, for example, prevent breakdowns, but also manage the entire production:
- reduce the percentage of defective parts: analyze why a marriage occurs and how to avoid it;
- optimize individual steps so that they take less time;
- use fewer materials for production, which means lower costs;
- monitor the condition of the equipment, record its efficiency and workload;
- automate individual stages of production.
Identifying security threats
Machine learning helps to make production safer by identifying minor changes in equipment operation and alerting of a possible disaster in time.
Usually in banks, the client’s creditworthiness is assessed by managers. Employees spend a lot of time on assessments and often make mistakes – they reject loans to those who could pay them and give them to those who are insolvent.
Banks and their clients regularly lose money due to fraudulent transactions. Machine learning helps to recognize such operations – special algorithms learn to detect signs of fraudulent operations and block them in time.
Improving customer service
The faster the registration process at the clinic goes through, the less queues, the more convenient it is for doctors to work and the more loyal patients are.
Applying Machine Learning to Retail and Marketing
Most of the conversations about machine learning revolve around virtual assistants and autonomous cars. But in fact, almost every website you interact with uses machine learning algorithms to accomplish some task. Large companies are not investing in machine learning because it’s on a whim or because they want to be the first to learn. They are investing because they have discovered the positive impact of such investments. And so innovation will continue. We learned how to predict in a timely manner the need for preventive maintenance of equipment through a rather simple machine learning mechanism – supervised learning, or “learning with a teacher.” Data science consulting helps to figure out the tasks.