This is not very simple to choose a machine learning method and letting it go wild on the data. Particularly, understanding the core business problem and objective of the outcome and frame accordingly is one of the vital factors in machine learning. A general approach is difficult to recommend without intimate knowledge of the data. However, it sounds like we need to formalize the aspects of your model. Following questions may help to decide on machine learning problem or…

One of our business units wants to target the competitors’ customers with personalized product/offer. To do that, Business needs to understand who are the prepaid/postpaid customer of the competitor to push the relevant and personalized product/offer and they don’t have this data. Now, this is a binary classification problem and we want to apply machine learning machine method to predict the likeliness of competitor customer to be prepaid or postpaid.

Steps in Data Science…

Unlike supervised learning, unsupervised learning not working with labeled data, it is not showing the machine the correct answer. Instead, it is using different algorithms to let the machine create connections by studying and observing the data. Learn much of this through study and observation. Learning and improving by trial and error is the key to unsupervised learning.

However, the Knowledge Discovery process is the field of data mining is concerned with the development…