Machine Learning Project from A to Z

In this Post I will go through the workflow of a full machine learning project with the california housing dataset as a full Machine Learning project, from A to Z, like it is described in the book “Hands-on Machine Learning with Scikit-learn & Tensorflow” by Aurelien Geron.

Table of Contents:

  • Import Libraries
  • California housing Dataset
  • Big Picture
  • Train/Test Split
  • Extensive Data Exploration
    • Searching for Correlations
  • Data Preparation
    • How to process Categorical Attributes and Text
    • Custom transfer
    • Feature Scaling
    • Pipelines for tranformation
  • Train Models
  • Fine Tuning
  • Evaluation
  • Summary


Unfortunately with WordPress, it is only possible to display a Jupyter Notebook in a small window. Therefore I you can only view it on github, because it is better displayed there.


Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.

2 thoughts on “Machine Learning Project from A to Z

Add yours

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

Website Built with

Up ↑

%d bloggers like this: