However, the implementation of an AI project is often not easy due to the high adaptability and complexity of the problems to be solved and requires time and expertise that only a limited number of experts have. It is therefore very important to make the best possible use of existing expertise in order to achieve a satisfactory result or proof of concept quickly.
The problem of limited expertise in the implementation of AI projects could now be solved by "Automated Machine Learning" (hereinafter AutoML). AutoML is an emerging field in the field of artificial intelligence that deals with the automation of the machine learning workflow. The aim of AutoML is to automate as many steps as possible in a machine learning project in order to shorten the development time and make it more efficient. To this end, automation tools and algorithms are used to automate the manual selection and configuration of algorithms and hyperparameters.
In principle, a machine learning workflow supported by AutoML comprises the same steps as a classic machine learning workflow. In addition, individual steps are automated. However, the automation of individual steps remains a challenge and cannot always be achieved to the same extent. For optimization, the steps of model selection and hyperparameter optimization are the most suitable, as they are non-specific and independent of the use case and are therefore considered the core of AutoML. In addition, there are efforts to automate further steps such as data cleansing, feature creation and selection, and explainability of predictions. AutoML can also support data scientists in some of these steps, especially when little or no domain-specific knowledge is required. For example, standard mechanical tasks such as the standardization of column entries can be performed during data collection and preparation.
AutoML solutions can be divided into three categories:
Thanks to its many years of experience in cloud computing, M&M can draw on the services of Azure Machine Learning and the integrated AutomatedML functionality when creating proof of concepts. By using these tools, M&M is able to achieve its goals quickly and efficiently while saving costs. Azure Machine Learning is a fully managed cloud service platform that simplifies the creation, training and deployment of machine learning models. The integrated AutomatedML feature provides automated modeling that replaces manual configuration of models and hyperparameters. This allows M&M to reduce development time and increase efficiency without compromising the quality of the results.
If you would like to find out more about the possible applications and functions of AutoML, please contact our team of experts.