Data Science Tutorials

The tutorial answers the most frequently asked questions about deep learning and explores various aspects of deep learning with real-life examples.

The data scientist's comprehensive guide to mastering PyCharm

Data cleaning is a very basic building block of data science. Learn the importance of data cleaning and how to use Python and carry out the process.

A brief guide for navigating Google Colab to carry out data science coding and collaborating with other data scientists.

Learn the basic and essential commands for SQL with examples and a workspace notebook to refer to.

This Python Streamlit tutorial is designed for data scientists and machine learning engineers who want to quickly build web apps without extensive web development knowledge.

PyCaret is an end-to-end machine learning and model management tool that exponentially speeds up the experiment cycle and makes you more productive.

The data.table cheat sheet helps you master the syntax of this R package, and helps you to do data manipulations.

Discover Python Trumania, a scenario-based random dataset generator library. Learn how to generate a synthetic and random dataset in this step-by-step tutorial.

We help simplify sentiment analysis using Python in this tutorial. You will learn how to build your own sentiment analysis classifier using Python and understand the basics of NLP (natural language processing).

In this Python tutorial, you'll tackle implicit and explicit data type conversion of primitive and non-primitive data structures with the help of code examples!

A list of Python resources for the eight statistics topics that you need to know to excel in data science