Data Science Tutorials

Learn how to use the .append() and .extend() methods to add elements to a list.

Learn about Object-Oriented Programming (OOP) along with R's objects, different classes like S3 and S4, along with its construction, creating its generic function with examples and many more.

Learn how to effectively use list comprehension in Python to create lists, to replace (nested) for loops and the map(), filter() and reduce() functions, ...!

Discover the power of regular expressions with this tutorial. You will work with the re library, deal with pattern matching, learn about greedy and non-greedy matching, and much more!

Learn in detail about the ifelse() function, including syntax, along with finding whether a number is odd or even, and finally, with an example to see whether a student passed or failed their exam.

Learn how to construct and implement Convolutional Neural Networks (CNNs) in Python with Tensorflow Framework 2

Learn about the factor function in R, along with an example, and it's structure, order levels, renaming of the levels, and finally, with the ordering of categorical values.

Build your recommendation engine with the help of Python, from basic models to content-based and collaborative filtering recommender systems.

This article covers different ways to import text files into Python using Python, NumPy, and Python’s built-in methods. It also covers how to convert these into lists.

Learn to read and write Excel files in Python using openpyxl. This guide covers formulas, charts, cell formatting, and worksheet manipulation with hands-on exam

Learn what variable scopes are all about and get familiar with the 'LEGB' rule. You will also deal with scenarios where you'll get to see the global and nonlocal keywords in action.

Learn all about R's matrix, naming rows and columns, accessing elements also with computation like addition, subtraction, multiplication, and division.