You have a huge dataset with hundreds or thousands of dimensions? For example the expression of 20.000 different genes in human cells? Or the hundreds of variables in an industrial production process? Dozen of ingredients and properties of your products? You’d somehow would like to get a grasp of your data? To see, what you have and don’t have and what’s inside your data? You would like to know what has been similar and what has been different? Find anomalies in the data?
We’ll help you with manifold learning methods at big data scale. These methods find the “intrinsic” dimensionality in your data, which is often much lower than the number of attributes and measurements, and map your data onto two or three dimensions that you can actually see and understand.
We have an proprietary implementation for learning such visualization from data which is based on our own deep neural auto encode networks; this methods beats any other alternative method available on the market or presently being researched.
Remember, the human visual system is still the world’s best pattern recognition system. Why not use it?
Thus, give us a try on your data, now!