AyushNet has been developing machine learning and business process management software with big data systems since July of 2012. The founder of AyushNet was co-organizing very popular Big Data Science Meetup ( http://www.meetup.com/Big-Data-Science/ ) and collaborating with founders and CEOs of many startup companies and customers in big data analytics areas. The founder made presentations at Hadoop Summit, 2014 for a Big Data Science event on the topic “Mathematical Shape of Big Data” (http://www.meetup.com/Big-Data-Science/events/169095862/) and inspired many data scientists to combine calculus and statistics for machine learning.
The advancements of the Internet of Things and the big data analytics systems need new model for analyzing large volumes of data from software systems, machines and embedded sensors used for application areas such as natural ecosystems, bioinformatics, smart homes, smart cities, smart cars, airplanes etc. These complex systems need efficient methods for near-real time collection, processing, analysis and sharing of data from and among the sensors, machines and humans. AyushNet patented and implemented a new model (CALSTATDN) for machine learning by iterating over a sequence of computing methods of calculus (CAL), statistics (STAT) and database normalization (DN) respectively, in order to reduce error and processing time of extremely large volumes of streaming data by several orders of magnitude. AyushNet implemented software for Smart Home Analytics system with CALSTATDN model and improved performance by 1000 times.
Here is a link to a presentation at Global big data conference: