Implementing Automated Machine Learning Systems with Open Source Tools

I've written a bit about automated machine learning in the past. I won't recap any of the introductory material what I have already covered, but if interested in running down the main points, as well as a foray into the practical, feel free to peruse these articles before moving on. Semantically, the training of a machine learning model, while the result of these automated steps, is incidental to the automated machine learning process, while automated steps such as model evaluation and model selection are ancillary to the core. This is all well and good, theoretically speaking. But what if you want to implement an automated machine learning pipeline of your very own, or automate particular aspects of a machine learning pipeline with respect to the 2 overarching tasks outlined above?