In machine learning, we seldom get datasets that are perfect from the beginning. Almost it never happens that we get the data and just feed into our machine learning algorithms. In fact, it is one of the final steps. Before we can use the data, we need to act on it. We need to clean, […] ...

In this article, we will take a look at how we can use image augmentation in deep learning. Data augmentation is a very useful technique when dealing with image data. Image augmentation is most helpful when the dataset is small. We can also benefit from image augmentation when we are not able to find any […] ...

In this article, we will take a practical approach to some basic image manipulation and transformation using OpenCV and Python. OpenCV is one of the best computer vision libraries and it is easy to use as well. If you want to become a master in the field of computer vision and deep learning, then OpenCV […] ...

Introduction In this article, we will take a look at the various aspects of the XGBoost library. XGBoost is one of the most reliable machine learning libraries when dealing with huge datasets. In my previous article, I gave a brief introduction about XGBoost on how to use it. This article will mainly aim towards exploring […] ...

XGBoost is a machine learning library that uses gradient boosting under the hood. As XGBoost uses gradient boosting algorithms, therefore, it is both fast and accurate at the same time. It is very efficient at handling huge datasets often having millions of instances. For this reason, XGBoost has become very popular in data science platforms […] ...