Tag: Data Science

Introduction Machine Learning and Artificial Intelligence have been weaved into our lives in some form. Every newcomer to the field is trying to solve machine learning problems. But I have a different take on it. I think that one should not try to solve machine learning problems. And I have a reason to think so. […] ...

Data preparation or processing is one of the most important steps when working with real-world data on a machine learning project. One of the major pains in such situations is working with categorical data. This is because most of the machine learning algorithms cannot work with categorical data directly. They are needed to be converted […] ...

Updated on April 19, 2020. The MNIST handwrttien digit data set has become the go-to guide for anyone starting out with classification in machine learning. But it is not only for students and learners. Even researchers who come up with any new classification technique also try to test it on this data. So, in this article, […] ...

In my previous article, Challenges in Machine Learning Project, I just touched upon the points of overfitting and underfitting. In this post, I am going to give a bit more in-depth view of the two. And if you are interested in Machine Learning, then you will surely enjoy this article about overfitting and underfitting. Overfitting […] ...

Starting a Machine Learning project can be really exciting and challenging as well. How? Suppose that, the company you are working for gets a project to design a predictive model for a huge organization. The model should be able to carry out predictive business analytics. And being the experienced engineer that you are, you get to lead the team […] ...