Easily develop machine learning projects in the cloud and extract valuable business insights using tools provided by IONOS.
Machine learning holds immense potential like no other analytical method. As a sub-discipline of AI, it enables you to extract valuable insights and knowledge from both existing and new data. Enhance future predictions and actionable recommendations by developing your own machine learning models, leveraging individual or pre-existing algorithms, all on the IONOS Cloud.
For example, offer your customers a significantly improved user experience with purchase suggestions and customised information.
Machine learning employs data analysis using models designed by data scientists. Through continuous exposure to training data, the system "learns" patterns within the data, guided by predefined algorithms.
Apply these machine learning models to specific tasks, enabling the extraction of valuable insights, predictions, and recommendations from extensive datasets.
In the machine learning lifecycle, two distinct phases exist: development and training, and inference or operational.
During the development and training phase, the data scientist builds the machine learning model using training data. Numerous tests and algorithm refinements are performed to ensure its accuracy. In the subsequent inference phase, machine learning engineers convert the model into a pipeline for specific tasks.
Various cloud products and open source tools are used to develop and deploy the pipeline:
With IONOS Cloud Compute Engine, you access the exact CPU and RAM power you need. Live vertical scaling allows you to flexibly adapt the resources of the IONOS Cloud IaaS platform. This means you can scale your machine learning environment or pipeline, even during runtime, without the need to restart VMs.
IONOS S3 Object Storage is a perfect cloud solution for big data analysis and machine learning. Seamlessly integrate and securely handle data within automated processes using the REST API or third-party SDKs.
Leverage PostgreSQL, one of the most highly acclaimed open-source databases, for your machine learning project. Easily set up databases on-demand through the Data Center Designer and access them via the Cloud REST API.
IONOS works with cloud native partners to provide tailored support throughout your machine learning project's entire lifecycle. From strategy, analysis, conception, and implementation to ongoing operations and further development of your unique solution.
Experienced IONOS partners such as b.telligent & codecentric implement big data and ML solutions for a wide range of use cases such as data engineering, data science or business intelligence. Their approach is built upon proven reference architectures, utilising cloud-native and cloud managed services whenever suitable.
If you’re using a European private or public cloud or Managed Kubernetes service from IONOS, you’ll benefit from open standards. These guarantee you full data and platform sovereignty and complies with all legal requirements.
Your data is stored in cost-efficient IONOS S3 Object Storage. The data platform is provided by our technology partner Stackable, and enables maximum service setup flexibility.
Harness the power of machine learning on the IONOS Cloud to predict customer behaviour patterns based on historical data. Generate personalised product suggestions and recommendations using machine learning algorithms in a streamlined pipeline.
Utilise powerful machine learning models to prevent credit card fraud. Train the models to recognise fraudulent behaviour from past transactions and seamlessly integrate them into the payment process for automated protection.
Avoid customer loss with an efficient machine learning pipeline on the IONOS Cloud. Model customer behaviour and identify potential churners using machine learning. Engage them with tailored offers to encourage retention.
IONOS data centres are ISO 27001-certified and offer geo-redundancy and exemplary data security.
IONOS relies on renewable energy, environmentally friendly travel and efficient, high-performance data centres.