Ensemble methods in Simple terms

One of my friends once spoke to me on how they assembled at a colleagues place in order to pool heads together and try to ace a skills screening test in codility. Their expectations must have been that they would produce more accurate answers together. On a sad note though, they all ended up not passing through for an interview.
While this might not be the exact replica of how ensemble methods work the analogy is the same together with what ensemble learning hopes to achieve which is better accuracy and more stable algorithms(models).
Ensemble methods are largely used with unsupervised learning algorithms when making predictions.
It is a technique that involves combining a diverse range of algorithms in order to come up with a better and more optimized output(better accuracy).
Ensemble methods have not only been known to improve the overall accuracy of the models but have also been very effective for winning competitions in which candidates are required to come up with the most accurate model.
For more visit https://datascienceafrica.medium.com/ensemble-methods-in-simple-terms-6dc1bef49907