The primary goal is to meet functional and non functional requirements, where heavy hard code to make sure the software performs what is intended.
The quality of the software depends on the quality of the code, the software does not come with a “brain”, it is humans that instruct what software program to perform all the tasks and output.
The software is created using one software stack such as Java, etc.
Machine Learning (ML)
In ML models the primary goal is to optimize the metric (accuracy, precision, etc) of the models. Improvement could bring significant business value creation, because with the deployment of machine learning models, it can use it to off load humans to make decisions and pick for the best value or parameter to optimize the result. This is particular so you can see it in the field like image manipulation or touch up that produce ML assisted on the certain tasks that provide on average much more precise, better and time saver improvement on the final output result.
The quality of the models depend on various parameters which are mainly related to the input data, the better the expert involvement in coming out with the best parameters optime setting and what kind and range of value use for the output optimization, the better the result will be for the final result generation as expected.
ML could be created using different algorithms and related libraries. Each of the algorithms could result in different performance.
This figure represents the different:
So the problem a company needs to solve to create a predictive model is to identify data samples for when the condition is true and when the condition is false and pass this data to a predictive algorithm to create the model. Involvement of the expert or high performance officer to understand how they perform their work and capture the rules they use is also one of the important inputs to capture. That is a simplistic way to look at predicting outcomes. We hope the above provides a quick way for you to understand and be able to differentiate convention and ML assist software. Be always asking if the said software comes with ML assist, you need to understand whether it is or just simply apply a fixed template that works for one scenario, but never for other. In general, machine learning (ML) can not run away from artificial intelligence (AI), it goes hand by hand.
E-SPIN Group in the enterprise ICT solution supply, consulting, project management, training and maintenance for customers and partners we served across the region. Feel free to contact E-SPIN for your specific operation or project requirement.