Data science-tutorials

Learn how to use ChatGPT in a real-life end-to-end data science project. We will use it for project planning, data analysis, data preprocessing, model selection, hyperparameter tuning, developing a web app, and deploying it on the Spaces.

In this Docker tutorial, discover the setup, common Docker commands, dockerizing machine learning applications, and industry-wide best practices.

A complete overview to understanding multiple linear regressions in R through examples.

Write your first bash script and learn the essentials: variables, functions, loops, and conditionals with working code examples.

A comprehensive introductory tutorial that will help you master the fundamentals of Julia. Learn about operators, conditional statements, working with DataFrames, and more.

Learn how to use the Power BI CALCULATE() function while giving examples of how you can use it.

Learn how to manage threads and processes with Python’s multiprocessing module. Discover key techniques for parallel programming. Enhance your code efficiency with examples.

Learn what an executable file is and how to convert a Python script to an .exe file using PyInstaller, Nuitka, and auto-py-to-exe.

Learn about the essential Python tools for software development, web scraping and development, data analysis and visualization, and machine learning.

A hands-on PySpark tutorial: install PySpark, explore data with DataFrames, and build a K-Means clustering model for customer segmentation.

Understand all the ins and outs of how to create Power BI heatmaps and their applications

Generating synthetic data using Python Faker to supplement real-world data for application testing and data privacy.