Machine Learning

Development by Anexia

Machine learning development by Anexia


Machine learning today is ubiquitous. Personalized product recommendations, language recognition, spam filters – each of these applications is based on machine learning. Given the enormous growth in the available data volumes, machine learning is an increasingly interesting aspect for businesses, since human evaluation of the data has become impossible. Each business has its individual requirements of a machine learning project. Our specialists support you as you develop a machine learning process and implement the necessary algorithms for you on the basis of the latest findings.

Machine learning development by Anexia
Use of machine learning
Use of machine learning

The fields of application for machine learning are diverse and they help with the optimization of processes. The basis for machine learning is data. Data and algorithms are used to detect patterns; from these, new, independent solutions to problems are derived. The more data there is, the more a system can learn. With the aid of machine learning, relevant data can be found, extracted and summarized. Accordingly, complex tasks can be “outsourced” to a machine, say, to detect an error in production, or in medicine, to help with the detection of tumors.

Using big data Using big data

So you’ve got a lot of data – big data? We can help you make constructive use of these large data volumes and to draw out all available information by means of machine learning. Our experience in the Python programming language makes us the ideal partner for machine learning development. Depending on the requirement, we can also use current open-source software or services such as Microsoft’s Azure ML.

Our finger on the pulse Our finger on the pulse

In our research and development division, our employees are constantly developing new ideas and potential applications. In the area of artificial intelligence and machine learning in particular, there are constantly new findings and tools. You can profit from our research and our experience from projects of all kinds.

Customer satisfaction and machine learning Customer satisfaction and machine learning

Not only can machine learning help your business to optimize processes and thereby increase turnover – it can also boost customer satisfaction. The data can aid in detecting customers’ needs, for example by issuing personalized advertising or quotes. Why not benefit from the possibilities offered by machine learning? Get in touch!


Let yourself be convinced by our references
Data and algorithms: the basis for machine learning
Data and algorithms: the basis for machine learning

Data is the basis for effective machine learning. With the aid of machine learning, a computer can build up an algorithm on the basis of datasets that can then be used to process the data. In simple terms, an algorithm is a recipe or set of instructions for solving a problem and consists of a large number of defined single steps. The process of arriving at an algorithm can be monitored or unmonitored. With monitored learning, patterns are detected through defined training examples and the knowledge thus obtained is then applied to new data. Through multiple passes, the network comes to learn how connections can be formed. On the other hand, with unmonitored learning, a model is created via the algorithm that describes the inputs, independently creates categories and derives predictions from these.

In principle, machine learning functions similarly to human learning. Just as we learn as children to recognize particular objects in a picture, the computer also learns to identify these objects. The more data is available to a system, the faster and better it can learn and then identify objects correctly. Mathematical and statistical models are used for the learning process. Here a distinction is made between two major systems. In symbolic approaches, the knowledge is represented explicitly. Sub-symbolic systems, on the other hand, use artificial neural networks that function similarly to the human brain and that represent the knowledge implicitly.

The datasets used as bases for machine learning can be highly diverse. They may include analog as well as digital data, media data such as audio, video, images and text, while even system logs and sensor data may also be used.

Machine learning offers businesses many advantages and possibilities for optimization. Make purposeful use of your data and create a competitive advantage for yourself.

Increased customer satisfaction
More insightful findings
Adaptability
Efficiency
Better business outcomes
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