Data Science Tutorials

Learn about Markov Chains, their properties, transition matrices, and implement one yourself in Python!

In this tutorial, you'll learn about and how to code in Python the probability distributions commonly referenced in machine learning literature.

In this tutorial, you'll learn about Support Vector Machines, one of the most popular and widely used supervised machine learning algorithms.

This tutorial will demonstrate how you can install Anaconda, a powerful package manager, on Microsoft Windows.

In this tutorial, you'll learn about the statistical concepts behind survival analysis and you'll implement a real-world application of these methods in R.

Learn about logistic regression, its basic properties, and build a machine learning model on a real-world application in Python using scikit-learn.

Python NLTK (natural language toolkit) sentiment analysis tutorial. Learn how to create and develop sentiment analysis using Python. Follow specific steps to mine and analyze text for natural language processing.

A hands-on tutorial for building and customizing line, bar, and scatter plots in Matplotlib using Python and real-world stock market data.

A NumPy tutorial for beginners in which you'll learn how to create a NumPy array, use broadcasting, access values, manipulate arrays, and much more.

This Keras tutorial introduces you to deep learning in Python: learn to preprocess your data, model, evaluate and optimize neural networks.

In this tutorial, you are going to learn how to create GUI apps in Python. You'll also learn about all the elements needed to develop GUI apps in Python.

In this tutorial, you will learn how to train generative models to compose music in TensorFlow 2.0.