Like any input-dependent system, machine learning (ML) is subject to the "garbage in - garbage out - garbage in" axiom. Clean and accurately labeled data is the basis for building any ML model. The ML learning algorithm understands patterns from valid ...
Today, people store their data in the cloud with applications such as Microsoft's OneDrive, Apple's iCloud, Google Drive, and Dropbox. There are many reasons why cloud technology is preferred, such as the storage space available, ease of use, and th...
Data is the new gold. Information is being collected from various sources: IoT devices, M2M communications, facial recognition software, etc. These vast data sets allow companies to understand customer needs better, identify significant correlations be...
Manual data processing, especially those involving numbers, has a high probability of human error. This process is not only time-consuming but also quite expensive. A practical solution is RPA, robotic process automation in the financial sector. Financ...
Software developers with valuable legacy products or portfolios are thinking about a question that has huge implications for their business.
When is the right time to upgrade a legacy software product?
Software modernization aligns the code base o...
A prototype is a sample model or preliminary version of the final product. It represents an initial version of an app in the pre-development stage.
User acceptance is the key to application success. Therefore, you should consult with your end-users ...