Machine Learning

Machine learning

In recent years, advances in hardware technology and software techniques have made it possible and practical for machine learning to provide better solutions to many real-world problems, even on embedded devices.

Nevertheless, embedded machine learning presents a unique set of challenges, including hardware resource requirements and performance considerations, the need for integration of specialized software technologies, and not least the learning curve – including a dependency on skill sets that are often not present in existing development teams.

Siemens Embedded's platform solutions and professional services enable our customers to get started quickly and easily with machine learning and allow them to focus on how machine learning can add value to their products, without first having to solve a bewildering and time-consuming array of complex platform-level challenges.

Machine Learning

In recent years, advances in hardware technology and software techniques have made it possible and practical for machine learning to provide better solutions to many real-world problems, even on embedded devices.

Nevertheless, embedded machine learning presents a unique set of challenges, including hardware resource requirements and performance considerations, the need for integration of specialized software technologies, and not least the learning curve – including a dependency on skill sets that are often not present in existing development teams.

Siemens Embedded's platform solutions and professional services enable our customers to get started quickly and easily with machine learning and allow them to focus on how machine learning can add value to their products, without first having to solve a bewildering and time-consuming array of complex platform-level challenges.

Sokol Machine Learning Add-On

Software and expertise enabling customers to get started quickly and easily with machine learning, without first having to solve a bewildering and time-consuming array of complex platform-level challenges. Along with key open-source technologies and productivity tools, security vulnerability monitoring and support, customers can move forward into machine learning with confidence.

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