We can help you frame, interpret, express or recompose business problems in ways that are well-aligned to deep learning approaches and technologies. Deep learning is a very powerful toolkit, but it does not suit not every business problem – sometimes its a simpler data problem or can be solved with math or statistics, or perhaps a different type of machine learning may be more applicable. Some business problems can be tackled with deep learning, but only if they meet certain criteria and are defined the right way.
Doing deep learning – better, can take many forms depending on your requirements. Some examples of the kinds of things that we can do to help include:
- Decompose your business problem in ways that provide ease of access to deep learning solutions – typically this involves some kind of complex data pattern recognition and the ability to create a prediction from unseen data as the result
- Investigate previous experiences by others and identify the state of the art of deep learning approaches for your specific application domain
- Evaluate the available data to drive deep learning, and augment it from other sources/techniques
- Optimise the data type and volume and sequence for deep learning model training with regard to accuracy (results) and speed (performance)