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The term 'big data' is known as a large and diverse group of information that is growing increasingly, and this includes its increasing size and speed in addition to the Read More >>

  The data team consists of a lot of professionals which include data analysts, data engineers, product managers, data scientists and machine learning engineers. In this article, I will explain Read More >>

Definition of the problem statement: This is the first step in a data science project. It’s a brief description of the kind of problem you are trying to solve. For Read More >>

Google Colab:  Google Colaboratory or “Colab” for short, is a product from Google Research. Google Colab allows anybody to write and execute arbitrary python code through the browser, and is Read More >>

  There are several python frameworks for data science. In this article, we will examine the popular ones. PyTorch: PyTorch is a framework that is perfect for data scientists who Read More >>

Data visualization is essential to analyze massive amounts of information and make data-driven decisions. Data Visualization involves producing images that communicate relationships among the represented data to viewers of the Read More >>

Data Science courses flood the internet at a very high price and some of  them ain't worth it. In this article, I curated a list of platforms that teach data Read More >>

As everything that is good has its bad side, Artificial Intelligence has its disadvantages. However we need to take care of it and ensure that the benefits are used to Read More >>

The advantages of Artificial intelligence cannot be overemphasized, we explained some of the benefits below: Reduction in human error: Humans are prone to make mistakes but machines that are programmed Read More >>