Python Tutorial

Discover the power of XGBoost, one of the most popular machine learning frameworks among data scientists, with this step-by-step tutorial in Python.

Learn about Pip, a powerful tool that helps you properly manage distribution packages in Python.

Learn how to use Python HTTP requests to interact with REST APIs. This guide covers GET and POST requests, examples, and best practices for API integration with a focus on the requests module.

Learn how to implement For Loops in Python for iterating a sequence, or the rows and columns of a pandas dataframe.

Learn about the f-string formatting technique in Python 3.6. In this tutorial, you'll see what advantages it offers and go through some example use cases.

Learn how to analyze data in the form of a dynamic quadrant chart in Tableau.

Learn how you can capture trends and make sense out of time series data with the help of a moving or rolling average.

In this tutorial, you'll learn how to implement power applications like Prisma using TensorFlow 2.0.

Explore basic math concepts for data science and deep learning such as scalar and vector, determinant, singular value decomposition, and more.

Learn about histograms and how you can use them to gain insights from data with the help of matplotlib.

Many Python users are familiar with using asterisks for multiplication and power operators, but in this tutorial, you'll find out additional ways on how to apply the asterisk.

To be an adept data scientist, one must know how to deal with many different kinds of data. Learn to read various formats of data like JSON and HTML using pandas.