Building models with artificial intelligence (AI) and implementing them in your business is currently extremely time-consuming and complex. With Kubernetes as a Service from Netstream, you can leave all the necessary calculations to the Kubernetes cluster, which takes a lot of the work off your hands.
Machine learning techniques are increasingly being used to simplify problems in our everyday lives. Various industries are utilizing this technology and have already achieved significant success in areas such as self-driving cars, image recognition, translation, speech recognition, gaming, and even medicine. Given the new possibilities, it is no surprise that the business world has quickly embraced this technology.
Building effective AI models and putting them into operation remains complex and time-consuming even today. The technology requires large data sets to be uploaded and processed. The machine learning model must then classify the data in order to recognize images, for example. The AI must then be "trained," which is particularly time-consuming. Once the model has learned enough, it is finally implemented in an app that can then be used directly.
Many companies simplify the life of data scientists or machine learning engineers by introducing various tools. such as Kubeflow or Neptunethat can speed up the process. This can significantly reduce the number of steps required and accelerate app development.
Kubernetes can further improve, simplify, and accelerate app development at this point: With Kubernetes as a Service, all calculations required for training the machine learning model can be outsourced to a Kubernetes cluster. The data scientist or machine learning engineer only has to worry about data cleansing and the actual code. The rest is handled by a Kubernetes-based tool.
With Kubernetes as a Service from Netstream , you Netstream such apps directly in the Netstream Cloud deploy them easily.
Advantages:
- Cloud computing power from the Cloud
- Kubernetes saves you time and complexity.
- Develop apps faster and bring them to market sooner.
- Distribute and utilize resources more effectively.
