Socrates, one of the greatest Greek philosophers of mankind, once said, “The unexamined life is not worth living.” This famous quote can be adapted to Machine Learning models as well. If this quote has to be rewritten to ML world, it will read as “The unexamined ML model is not worth-production.” An important aspect of the predictive modeling pipeline is, measuring the performance of the model developed. It determines how best the model fits the purpose. The performance of model is measured by running the model on unseen dataset and comparing the output with actual results. There is no one typ ..read more

Compressive strength is one of the characteristics of concrete, which can be described as the amount of load it can withstand before gets broken into pieces. Mathematically, it can be represented as The unit of compressive strength is denoted as Pa (Pascal). Problem Statement The compressive strength of concrete is a non-linear function, and it varies based on the ingredients it contains and the number of days it is allowed to settle. In the construction industry, before the columns and pillars are constructed, multiple concrete blocks are manufactured with different ingredients and are a ..read more

One of the widely used techniques to identify all the important features from a given dataset is Backward Elimination, which is discussed in the post How to identify the features that are important for a Machine Learning model?. With this technique, a model has to be developed each time to determine the importance of all the features and eliminate the least important one. As only one feature gets eliminated during each iteration, the model has to be re-trained every time a feature gets eliminated, till all the insignificant features are removed. This technique is, certainly, a computationally ..read more