Although it is tempting to use popular algorithms like extreme gradient boosting/XGBoost, the algorithm of choice for winning Kaggle competitions, it might not be the best choice for the problem at hand, always. Having a logical, time tested approach to selecting algorithms and the right configuration of the algorithm for a dataset by tuning the hyper parameters is what moves Machine learning from the sphere of science to art.

Photo by Javier Allegue Barros

In machine learning, there is no “one size fits all” solution. Choosing the algorithm is a comprehensive task that demands the analysis of a variety of factors. That is why it…

Velaga Chaitanya

Life long learner with a strong inclination towards emerging technologies. Co founder, DscvryAI

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