MyDataModels: Small Data Machine Learning for Every Professional
Follow MyDataModels on :
Simon Gazikian, CEO
Big data dominates the current business markets as many companies strive to implement machine learning and gain an edge in the market. However, the truth is, most employees and even domain experts in different industries have a superficial knowledge of big data at most. Moreover, these professionals handle the massive amount of small data that is available within their premises for their day to day operations. In such a scenario, it goes without saying that companies should focus on making the most of their small data by overlaying machine learning on it. Sounds difficult? MyDataModels makes it simple. Driven by the motto of empowering every professional with access to machine learning, MyDataModels is already making waves by helping some of the biggest companies in the world to improve their decision making through its machine learning platform for small data.
Currently, MyDataModels is assisting Gemalto, a reputed manufacturer of smart cards for secured payments, to improve and optimize the efficiency of the qualification and manufacturing process controls used for its products. The firm produces smart cards in batches using equipment of different types, each having a different set of parameters. Aware of the consequences of incorrect assessments, Gemalto aims to calibrate the parameters of the equipments involved in the manufacturing process before delving into predicting the outcomes of the smart cards production.
We make small data talk, and give machine learning access to every professional
TADA, MyDataModels’ machine learning platform, is helping Gemalto’s domain experts with limited or no machine learning skills to build and run their predictive models and achieve fruitful results.
But how does TADA do it? TADA is designed to build predictive models based on an organization’s small data. A firm needs to collect or import small datasets and upload them into TADA to generate the predictive model in a matter of hours. “We develop predictive models that can function on any platform, including cloud, desktop, mobile, edge devices, and embedded environments,” mentions Gazikian. “At the heart of TADA is the engine which is a re-engineered and commercialized form of evolutionary algorithms,” says Simon Gazikian, CEO, MyDataModels.
While MyDataModels has PhDs who are focused on streamlining the performance of TADA, their flagship platform, the company seeks to work with its partners, including academia, to cater to the evolving needs of its rapidly expanding clientele. The company is adding new features and mathematical updates to make the platform more agile and flexible. As demand grows for edge computing, machine learning will have a more significant role to play in the embedded systems arena. MyDataModels, with TADA, its machine learning platform for small data, is aptly positioned to cater to this demand in the coming years.
Gazikian equates the ease-of-use of their platform to that of MS Excel. In addition, predictive models produced by TADA are natively in C++ or Java languages and directly executable within any application, from cloud to edge computing environments. MyDataModels allows prospective clients to run a free trial for two weeks before investing in the solution.
MyDataModels aims to emerge as the ‘unicorn’ of small data machine learning in the next three to five years and expand its clientele. The company also has plans to extend its machine learning prowess to the US and APAC regions and help more companies attain greater value from their existing data.
This content is copyright protected
However, if you would like to share the information in this article, you may use the link below: