Data Science Tutorials

Learn how to perform computational and statistical analysis on the results of your biological experiment.

In this tutorial, you'll try to gain a high-level understanding of how SVMs work and then implement them using R.

Get introduced to Asymptotic Analysis. Learn more about the complexity of the algorithm as well as asymptotic notation, such as Big O, Big θ, and Big Ω notation. Along with the examples of complexity in a different algorithm.

Learn about Market Basket Analysis & the APRIORI Algorithm that works behind it. You'll see how it is helping retailers boost business by predicting what items customers buy together.

Learn how to use Highcharter to create a visualization that creates a buzz.

Learn how to remotely send R and Python execution to a SQL Server from Jupyter Notebooks.

Learn how to build dashboards in Python using Dash.

This tutorial covers what a parameter and a hyperparameter are in a machine learning model along with why it is vital in order to enhance your model’s performance.

Analyze employee churn. Find out why employees are leaving the company, and learn to predict who will leave the company.

This tutorial will demonstrate how you can make datasets in CSV format from images and use them for Data Science, on your laptop.

Master applying PCA in R in this tutorial. Normalize data, compute principal components with princomp(), and visualize results with scree plots and biplots.

In this tutorial, you will learn exclusively about Python if else statements.