Episode

Set up your Jupyter Notebooks to start building regression models (Part 6 of 17) | Machine Learning for Beginners

with Bea Stollnitz

Machine Learning for Beginners

In this tutorial, we'll walk you through the process of setting up a Jupyter notebook using a virtual environment for machine learning projects. This video is part of our Machine Learning for Beginners series, and we'll be using Jupyter notebooks for most of our future videos in this course.

In this video, presented by Bea Stollnitz, Principal Cloud Advocate at Microsoft, you'll learn:

  • How to work with Jupyter notebooks in VS Code
  • How to clone and navigate through the GitHub project we'll be using in this series
  • How to create a virtual environment using Python's venv module
  • How to install commonly used data science and ML packages in the virtual environment
  • How to set up and use the virtual environment in your Jupyter notebook

Stay tuned for the next video in this series, where we'll dive deeper into various machine learning topics and guide you through their implementation using Python code in Jupyter notebooks. See you there!

Chapters

  • 00:00 - Introduction
  • 00:54 - How to run the Jupyter notebook in a GitHub Codespace
  • 01:07 - How to run the Jupyter notebook locally
  • 01:43 - What is a Jupyter notebook?
  • 02:33 - Install Python packages in a virtual environment
  • 03:32 - The Python packages for ML - pandas, matplotlib, numpy, scikit-learn, ipykernel
  • 04:20 - Use the virtual environment in a Jupyter notebook in VS Code
  • This course is based on the free, open-source, 26-lesson ML For Beginners curriculum from Microsoft.
  • The Jupyter Notebook to follow along with this lesson is available!

Connect

Azure Machine Learning
Python