SensiML™ Corporation, a leading developer of AI tools for building intelligent IoT endpoints, has released a new web-based AutoML tool with a simple but powerful user interface which makes it easier than ever for developers to implement AI for their endpoint IoT applications. This new tool is an evolution of the company’s industry-leading Analytics Studio, a core component of the SensiML Analytics Toolkit Suite.
The new SensiML Analytics Studio is a standalone web-based application designed for users without data science expertise. Since it is a browser-based tool, there is no need for developers to download or install software locally. It features UI-driven AutoML capability with sophisticated but intuitive controls, allowing users to quickly configure the software, obtain results, tune and iterate. New visualization and reporting features provide clear and easy-to-understand feedback.
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For data scientists and machine learning experts, SensiML will continue to provide a separate version of the tool with a Python language interface. This version, called SensiML Analytics Studio Notebook, gives users programmatic access to SensiML Cloud and all of its associated functionality for building optimized ultra-compact ML sensor algorithms for consumer, industrial, automotive, and commercial, and agricultural IoT applications.
Both versions of Analytics Studio will also continue to complement The SensiML Analytics Toolkit Suite which provides a complete design flow for developers to build intelligent endpoints from start to finish, including raw signal capture, data insight labeling, algorithm generation, firmware code generation, and test/validation and support.
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“The SensiML Analytics Toolkit was designed to simplify developing AI for IoT applications – making it possible for a single user or small development team to implement a complete AI-based solution for IoT endpoints,” said Chris Rogers, SensiML CEO. “The new browser-based Analytics Studio improves the user experience through a sophisticated yet simple to use interface, so building intelligent sensor algorithms is easier than ever.”
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