IMPROVE THE ACCURACY OF PREDICTED OUTCOMES
Machine Learning, a category of algorithms, assists in making software applications more accurate. In effect predicting outcomes without being explicitly programmed. Machine learning algorithms receive input data and use statistical analysis to predict an output. Simultaneously updating outputs as new data becomes available.
To begin with, an algorithm is the procedure (formula) for solving a problem. Specifically to conduct a sequence of specified actions. In computer science, an algorithm usually means a small procedure that solves a recurrent problem.
The processes involved in machine learning are similar to that of data mining and predictive modelling. Above all, these processes involve sifting through data in order to recognize patterns. Consequently adjusting program actions accordingly. For example, repeat marketing on the internet involves machine learning. For the reason that your previous search data is used to serve similar content and ads to you. Indeed, based on your previous search patterns and purchases. The capabilities of machine learning include fraud detection, spam filtering, network security threat detection, predictive maintenance and rotating news feeds.
How it works
There are two categories of machine learning algorithms which are supervised or unsupervised. Supervised algorithms require a data scientist or data analyst. These experts provide both input and desired output. For the purpose of providing feedback of accurate predictions during algorithm ‘training’. Data scientists determine the variables which should be used and analysed by the model in order to ‘learn’ and make predictions. Once training is complete, the algorithm will apply what was learned to new data.
Unsupervised algorithms are not ‘trained’ with the provision of the desired outcome data. Instead, the computational approach called deep learning is used in order to review data and deduce certain conclusions. Moreover, unsupervised learning algorithms implement more complex processing tasks than supervised learning systems. This includes image recognition, speech-to-text and natural language generation. The algorithms work by sifting through countless examples of training data and then automatically identifying subtle correlations between many variables. Once trained, the algorithm can use its cache of associations to interpret new data.
NBS Digital Technologies have the knowledge, skills and the necessary technological partnerships, to be able to digitally transform your business through the implementation of Machine Learning.