In mathematics, convolution is a mathematical operation on two functions that produces a third function expressing how the shape of one is modified by the other. In our service, raw data or automated convolutional results can be used as input training materials for deep learning.
For commercial application, because the influence of time on the data must be considered, recurrent neural network (RNN) is mainly used as the learning method. Normally, long short-term memory (LSTM) networks are well-suited to classifying, processing and making predictions based on time series data.
We not only use deep learning models to predict the data customers need, but also help customers explore the meaning and blind spots of data feedback. With the actual verification of the data, we look forward to making the algorithm and prediction data more usable.
The challenge for managers is to find the mix of practices that actually works.Harvard Business Publishing, 2020
We keep learning the most innovative technology, and also explore the most stable method, so that customers can obtain the most suitable information technology tools through our service.
Understanding customer needs is as important as IT capabilities. Our team is composed of a variety of cross-disciplinary talents who can smoothly communicate needs and results with customers.
In business, time also affects the work efficiency of customers, so we will try our best to make the information technology results reach the operational goals within the expected time.