Bitbloom launches Sift Learn to drive Machine Learning adoption in renewables
Bitbloom is delighted to announce the launch of Sift Learn. Sift Learn is a new product that puts powerful Machine Learning (ML) tools at the fingertips of analysts, engineers, and other domain experts in the wind industry. It addresses several practical barriers to machine learning adoption:
Allows domain experts with a large quantity of data to access advanced analytics capability through machine learning without needing specialist software skills to build their own data pipeline platform.
Provides a low-/no-code environment to leverage a rich set of ML tools, including high-quality ML algorithm implementations and cloud computing, while facilitating rapid experimentation and iteration.
Cuts down the time and cost for successful experiments to make it into production scenarios through integration with Sift Monitor, Bitbloom’s product for monitoring and dissemination of advanced analytics.
The product is the result of an 18-month collaboration, part-funded by InnovateUK, with ORE Catapult who have provided testing and feedback from data science experts. The ORE Catapult engineers have demonstrated the use of Sift Learn through three case studies, covering fatigue loading prediction, lost yield estimation and yaw misalignment, showcasing how ML can be used to tackle some of wind energy’s pressing data analytics needs. Keep an eye on the Bitbloom blog in the coming months when we’ll be publishing many more in-depth studies.
We are currently looking for companies to trial Sift Learn and experience the difference that ML can make to their analytics - if your organisation is interested taking part please reach out to info@bitbloom.tech.