Machine Learning Solutions


01 - The challenge


The challenge

Today's data-driven expectations place an increasing demand for the application of an integrated automatic decision model based on machine learning in the case of modern software. During its complex learning, Machine Learning (ML) can confidently absolve complex decision-making processes in hundredths of a second, which consumes extra time for human control and often presents the operators with an opaque, complex consideration situation, and cannot serve even a sudden increase in demand in this way. By applying ML, operators can receive decision-supporting information or outsource it entirely to machine learning, which greatly speeds up and facilitates their work.

02 - The solution


The solution

AWS’s ML portfolio provides effective and innovative solutions for typical machine learning problems as well as unique learning problems. For typical problems such as time-based prediction for statistical data, image content filtering and moderation, and many other areas, we can use pre-trained, high-accuracy models by calling programming interfaces in AWS. These interfaces are closely integrated with other AWS components, so for example, by using the TC2 Serverless accelerator, the ML function can be included in an easily integrated system. If the ML function is of a special, non-typed nature, AWS Sagemaker provides optimization tools for the entire life cycle of ML development and follow-up.
AWS Bedrock provides users with a generative AI platform with an ever-increasing number of AWS and 3rd party developed Large Language Models (LLM) available for use-based, immediate deployment. The support for independent providers, complemented by the transparent and secure data management model already familiar from AWS, provides a reliable environment for a company of any size and industry to test and deploy generative AI projects in a productive system.
TC2 can also support the early planning, implementation and operation phases based on proven best practices.