Hands on Automated Machine Learning for Beginners

Apply AutoML hands on in Python


   Machine Learning, Analytics & Automation, Development, Data Science and AI ML

  Language - English

   Published on 04/2022

  • Download the resources for the course
  • 2 AutoML hands on for beginners intro
  • 3 Auto EDA
  • 4 The 1st AutoML Library Regression example
  • 5 The 1st AutoML Library Classification example
  • 6 The 2nd AutoML Library Regression example
  • 7 The 2nd AutoML Library Classification example
  • 8 The 3rd AutoML Library Regression example
  • 9 The 3rd AutoML Library Classification example
  • 10 The 4th AutoML Library Regression example
  • 11 The 4th AutoML Library Classification example
  • 12 The 5th AutoML Library Regression example
  • 13 The 5th AutoML Library Classification example
  • 14 The 6th AutoMLLibrary Regression example
  • 15 The 6th AutoML Library Classification example


What is Automated Machine Learning (AutoML)

Will Automated Machine Learning replace Datascientists?

How to use AutoML in python

What AutoML options are available and free to use?

If you are a beginner and want answers to those questions and try AutoML yourself then this course is for you.

Here we go through various AutomatedMachine Learning (and Deep Learning) frameworks which are currently available (not an extensive list of course there are many more).

The main goal is to get an overview of what AutoML is and how to use it in python. We focus on free AutoML libraries instead of commercial ones so that you can follow along and try them yourself. The course has demo datasets for regression as well as a classification task so we see both supervised learning tasks for each AutoML libary we are going to cover.

Feel free to try out Automated Machine Learning with your own data as well

For this course you should have used Python before (Even AutoML requires us to write a tiny little bit of code)

Please also understand what this course is not

This course does not offer:

A basic introduction to what is ML/DL or an introduction to python

An in-depth  theoretic dive into each hyperparameter which can be adjusted / tuned

An all-in-one solution for every project you want to take in the future

This course does offer:

hands on code examples on how to apply those libraries on demo datasets

Specific relevant information for each library you need to be aware of when you use it

Helpful tools for any data scientist of business person who wants to reduce redundant and repetitive tasks and free some time to focus on the main steps in the data science life cyclle

What Will I Get ?

  • A hands on overview of free python automl packages and how to use them
  • You can apply AutoML packages on your own projects afterwards
  • practise with hands on code example on how to apply those libraries on demo datasets


  • We only use free AutoML libraries
  • This course is for beginners and data analysts / data scientists who want to learn AutoML packages in  Python
  • Python knowledge is helpful - this is not a "learning python" class
  • AutoML requires us to write some python code but not a lot
  • We use google colab so no need to install any software on your own device (if you don't want to)
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