The use of artificial intelligence by businesses is not a new concept. Anyone who has used Facebook, Google, Netflix, or Amazon is well aware of the tailored approach these companies use based on customer habits. And the use of customer driven data is not confined to high-tech companies alone. Businesses of all types apply machine learning to help drive a wide variety of decisions on marketing, product development, security, and even email spam filters.
One of the latest advances in artificial intelligence is deep learning. Deep learning uses neural networks to process enormous sets of data for diverse types of applications. For example, deep learning is used by autonomous cars for navigation, by security teams for video processing, and even to predict the result of court cases. All very impressive uses of deep learning, but can it solve more practical business problems? The answer is yes, of course, but like any tool deep learning must be used properly to be most effective.
Use Relevant and Clean Data
It seems obvious, but the first step to using machine learning of any type, including deep learning, is a good set of data. For example, if you want to predict the purchasing habit of 20 to 30 year old men for your latest cologne, don't use data from five years ago that includes women customers.
Consider the Context
Using the cologne example, maybe the data you use shows a dramatic increase in the number of sales within the last year due to a promotion. Deep learning may over-predict the amount of cologne to market to existing customers based on raw data alone, if you ignore the context.
Continuously Revise Your Algorithm
Like any engineering tool, deep learning algorithms need to be revised and updated to reflect your business model. Plan for the long term and consistently upgrade hardware and software to get the most out artificial intelligence. Regular maintenance is key for top performance.
Use the Right Tools for the Job
The software used to develop deep learning solutions continues to evolve very rapidly. Finding the right combination of frameworks, tools, and libraries can be a real challenge. Make sure you have a viable plan for keeping all of the various modules up to date and interoperating properly and you will spare your data scientists a lot of headaches.
Bright Computing has the software you need to set your business up with flexible and robust machine learning solutions designed to meet your specific needs. Our software helps to turn your data into action.