How to apply Machine Learning in companies?
How to apply Machine Learning in companies?
The rise of Artificial Intelligence and Big Data are giving a boost to the 4.0 revolution but behind these concepts is a huge amount of new terminology and new jobs that did not exist 10 years ago and one of these fields is Machine Learning.
What is Machine Learning?
Machine Learning (ML) is a branch of machine learning. artificial intelligence whose aim is to develop techniques that will enable computers to learn (performing one or more tasks autonomously) with prior training. It consists of letting algorithms discover patterns from a set of examples (data). This data can be numbers, words, pictures, statistics, etc. The ML algorithm finds patterns in them in order to provide some kind of relevant information (inference). The resulting models or programs must be able to generalise behaviours and inferences to a larger (potentially infinite) set of data. To understand this better, here is an example:
There is a training period for the algorithm in which the algorithm learns the guidelines for solving a given problem. Then, the algorithm is able to infer a new case from the trained data. By detecting patterns in that data, algorithms learn and improve their performance in executing a specific task. in an autonomous way or make predictions from data and improve its performance over time. Once trained, the algorithm will be able to find patterns in new data.
Types of Machine Learning
There are three types of Machine Learning depending on the level of supervision they require:
- Supervised LearningAs the name suggests, these are Artificial Intelligences that need some human control. In these cases, the Data Scientist establishes what type of data must be related to certain specific elements so that the machine can do the rest of the work. The professional must be in charge of introducing the inputs and outputs so that the technology can find patterns in the information.
- Unsupervised LearningIn these cases, the data is not pre-labelled and the AI has much more autonomy. It is the machine that must find the relationship and structure of the information. A higher density of information is obtained, but the sample is much larger, so it will be the Data Scientist who will be responsible for filtering it later.
- Reinforcement LearningThis system is very different from the two previous ones. Basically, it works with a "reward" system. When the machine gets its operations right, it is given a positive stimulus, and if it fails, it is given a negative one. Thus, by trial and error, the machine generates patterns and learns for itself what is the best way to proceed according to the needs of the organisation.
After seeing the advantages of this tool, we can say that the investment of having Machine Learning in the company can be extremely profitable. However, the capabilities and budget of the organisation must be taken into account, as it is a costly and complex technology.
How to use Machine Learning in business?
There are several advantages that Machine Learning can bring to companies, in general this technology facilitates the analysis of data and helps companies to obtain more and better insights. The technological impact of Machine Learning extends to various areas such as intelligent product manufacturing, customer service, fraud detection, warehouse management, etc. Machine Learning is emerging as a breakthrough in the digital transformation of companies. Above all, within the framework of Industry 4.0, as it is constantly learning and introducing constant improvements.
Business benefits and improvements
- Improved customer service, for example, by analysing customer preferences to offer personalised products automatically. This improves their perception of the company and enhances customer loyalty.
- It serves to reduce errors by applying machine learning to the management systems applied in the organisation, helping to ensure that mistakes are not repeated. The longer it has been integrated into the system, the more robust it will be.
- Another advantage is that it helps in fraud detection. Artificial Intelligence can easily detect which transactions are legitimate and which are not if we assign a pattern to these monetary movements.
- Process automation: The automation of routines or mechanical tasks that do not add value is a recurring element in the lists of benefits related to Artificial Intelligence. Thanks to Machine Learning, the machine will know which processes to handle and, over time, will refine them and even expand the number of tasks to be performed.