The optim*um service
- Deep learning is when software learns to recognize patterns in the (digital) representation of images, sounds and other data.
- When training a neural network, feature representations are learned layer by layer so that images or objects from the system, for example, can be properly recognized with higher probability.
- A significant driver of deep learning is the availability of large datasets and the ever-improving hardware. They enable models to be trained with many millions of parameters.
- Over the last ten years there have been spectacular breakthroughs in many application areas, such as image and language recognition, text analysis and AI gaming.
What makes *um better?
We believe there is no such thing as a ready-made solution. For our clients we develop customized deep learning solutions based on state-of-the-art processes. We deploy the right architecture for different problem domains, for example convolutional neural networks (CNNs) for image recognition or recurrent networks (RNNs) for analyzing sequences such as time series. This approach ensures each client receives the optimal solution, whether that is B2C or B2B.
Our Data Science Team possesses extensive sector-spanning experience in the field of machine/deep learning. With a mix of mathematicians, psychologists, physicists and computer scientists, the team is able to examine the various facets of a data problem from a wide range of angles. We stay on the cutting edge of research and do not shy away from technical innovations.