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.
Example: Offer your customers a significantly improved user experience with purchase suggestions and customized 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.
For developing and deploying the pipeline, a range of cloud products and open source tools are utilized:
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 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.
The Cloud offered by IONOS works with Cloud Native Partners, offering 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 Cloud partners like b.telligent & codecentric specialize in implementing big data and ML solutions across various use cases, including data engineering, data science, and business intelligence. Their approach is built upon proven reference architectures, utilizing Cloud-native and cloud managed services whenever suitable.
Using IONOS private or public cloud or Managed Kubernetes service ensures adherence to European open standards. You'll gain full data and platform sovereignty, meeting all legal requirements.
Your data is cost efficiently stored in IONOS S3 Object Storage, provided by our technology partner Stackable, offering maximum service setup flexibility.
Harness the power of machine learning on IONOS Cloud to predict customer behavior patterns based on historical data. Generate personalized product suggestions and recommendations using machine learning algorithms in a streamlined pipeline.
Utilize IONOS Cloud's powerful machine learning models to prevent credit card fraud. Train the models to recognize fraudulent behavior from past transactions and seamlessly integrate them into the payment process for automated protection.
Avoid customer loss with an efficient machine learning pipeline on IONOS Cloud. Model customer behavior and identify potential churners using machine learning. Engage them with tailored offers to encourage retention.
IONOS data centers provide exemplary data security with ISO 27001 certification and geo-redundancy.
IONOS prioritizes the green initiative through the use of renewable energy, eco-friendly travel, and high-performance data centers.